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Commit 1310ec3c authored by Bridget Tripp's avatar Bridget Tripp
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Updated version of final project

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%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
import numpy as np import numpy as np
import pandas as pd import pandas as pd
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from sklearn.model_selection import GridSearchCV from sklearn.model_selection import GridSearchCV
from sklearn.pipeline import Pipeline from sklearn.pipeline import Pipeline
from sklearn.svm import LinearSVC from sklearn.svm import LinearSVC
from sklearn import preprocessing from sklearn import preprocessing
from sklearn.decomposition import PCA, NMF from sklearn.decomposition import PCA, NMF
from sklearn.metrics import average_precision_score from sklearn.metrics import average_precision_score
from sklearn.feature_selection import SelectKBest, chi2
from sklearn.metrics import classification_report
from sklearn.model_selection import train_test_split
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
soma_data = pd.read_csv('preop_soma_all.csv', header=None).T soma_data = pd.read_csv('preop_soma_all.csv', header=None).T
np_data = np.array(soma_data) np_data = np.array(soma_data)
soma_data.columns = np_data[2] soma_data.columns = np_data[2]
#y = soma_data.iloc[13:len(soma_data),1] #y = soma_data.iloc[13:len(soma_data),1]
y = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1] y = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1]
X = soma_data.iloc[13:soma_data.shape[0],2:soma_data.shape[1]] X = soma_data.iloc[13:soma_data.shape[0],2:soma_data.shape[1]]
X = preprocessing.normalize(X, norm='l2', axis=0) X = preprocessing.normalize(X, norm='l2', axis=0)
#X = np.log(X)
``` ```
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
#partition data into test and train #partition data into test and train
from sklearn.cross_validation import train_test_split
X_train, X_test, y_train, y_test = train_test_split( X_train, X_test, y_train, y_test = train_test_split(
X, y, test_size=0.25, random_state=0) X, y, test_size=0.30, random_state=0)
``` ```
%% Output
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.
"This module will be removed in 0.20.", DeprecationWarning)
%% Cell type:code id: tags: %% Cell type:code id: tags:
``` python ``` python
pipe = Pipeline([ pipe = Pipeline([
('reduce_dim', PCA()), ('reduce_dim', PCA()),
('classify', LinearSVC()) ('classify', LinearSVC())
]) ])
N_FEATURES_OPTIONS = [26] #[25, 50, 75, 100] N_FEATURES_OPTIONS = [2, 3, 5, 10, 25, 26, 50, 75] #[26, 50, 75, 100]
C_OPTIONS = [(n) for n in range(1,6)] C_OPTIONS = [1, 2, 3, 4, 5, 10] #[(n) for n in range(1,6)]
LOSS_OPTIONS = ['squared_hinge','hinge'] #LOSS_OPTIONS = ['squared_hinge','hinge']
param_grid = [ tuned_parameters = [
{ {
'reduce_dim': [PCA(iterated_power="auto")], 'reduce_dim': [PCA(iterated_power=7)],
'reduce_dim__n_components': N_FEATURES_OPTIONS, 'reduce_dim__n_components': N_FEATURES_OPTIONS,
'classify__C': C_OPTIONS, 'classify__C': C_OPTIONS
'classify__loss': LOSS_OPTIONS },
{
'reduce_dim': [SelectKBest(chi2)],
'reduce_dim__k': N_FEATURES_OPTIONS,
'classify__C': C_OPTIONS
}, },
] ]
reducer_labels = ['PCA']
grid = GridSearchCV(pipe, cv=5, n_jobs=1, param_grid=param_grid, refit='AUC') scores = ['precision', 'recall']
grid.fit(X_train, y_train)
for score in scores:
print("# Tuning hyper-parameters for %s" % score)
print()
grid = GridSearchCV(pipe, cv=5, param_grid=tuned_parameters, scoring= score)
grid.fit(X_train, y_train)
print("Best parameters found on training set:")
print()
print(grid.best_params_)
print()
print("Grid scores on training set:")
print()
means = grid.cv_results_['mean_test_score']
stds = grid.cv_results_['std_test_score']
for mean, std, params in zip(means, stds, grid.cv_results_['params']):
print("%0.3f (+/-%0.03f) for %r"
% (mean, std * 2, params))
print()
print("Detailed classification report:")
print()
#print("The model is trained on the full development set.")
print("The scores are computed on the test set.")
print()
y_true, y_pred = y_test, grid.predict(X_test)
print(classification_report(y_true, y_pred))
print()
print(grid.predict(X_test)) print(grid.predict(X_test))
print(y_test) print(y_test)
print('Score: {0:0.2f}'.format(grid.score(X_test,y_test))) print('Score: {0:0.2f}'.format(grid.score(X_test,y_test)))
y_score = grid.decision_function(X_test) y_score = grid.decision_function(X_test)
average_precision = average_precision_score(y_test, y_score)
print('Average precision-recall score: {0:0.2f}'.format(
average_precision))
```
%% Output
[1 0 0 1 1 1 0 0 0]
[1, 1, 0, 1, 1, 0, 0, 0, 0]
Score: 0.78
Average precision-recall score: 0.59
%% Cell type:code id: tags:
``` python
#grid.get_params().keys()
print(grid.best_estimator_)
#cv_dict = grid.cv_results_
#average_precision = average_precision_score(y_test, y_score)
#print('Average precision-recall score: {0:0.2f}'.format(
# average_precision))
``` ```
%% Output %% Output
Pipeline(memory=None, # Tuning hyper-parameters for precision
steps=[('reduce_dim', PCA(copy=True, iterated_power='auto', n_components=26, random_state=None,
svd_solver='auto', tol=0.0, whiten=False)), ('classify', LinearSVC(C=1, class_weight=None, dual=True, fit_intercept=True,
intercept_scaling=1, loss='squared_hinge', max_iter=1000, /home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
multi_class='ovr', penalty='l2', random_state=None, tol=0.0001, 'precision', 'predicted', average, warn_for)
verbose=0))]) /home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
/home/otu/btripp2/.conda/envs/py36/lib/python3.6/site-packages/sklearn/metrics/classification.py:1135: UndefinedMetricWarning: Precision is ill-defined and being set to 0.0 due to no predicted samples.
'precision', 'predicted', average, warn_for)
Best parameters found on training set:
{'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
Grid scores on training set:
0.180 (+/-0.480) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.140 (+/-0.376) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.460 (+/-0.627) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.460 (+/-0.627) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.460 (+/-0.627) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.460 (+/-0.627) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.153 (+/-0.421) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.296 (+/-0.777) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.436 (+/-0.627) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.436 (+/-0.627) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.436 (+/-0.627) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.436 (+/-0.627) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.153 (+/-0.421) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.376 (+/-0.740) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.436 (+/-0.627) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.436 (+/-0.627) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.436 (+/-0.627) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.436 (+/-0.627) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.153 (+/-0.421) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.376 (+/-0.740) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.436 (+/-0.627) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.436 (+/-0.627) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.436 (+/-0.627) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.436 (+/-0.627) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.153 (+/-0.421) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.376 (+/-0.740) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.436 (+/-0.627) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.436 (+/-0.627) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.436 (+/-0.627) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.436 (+/-0.627) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.153 (+/-0.421) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.376 (+/-0.740) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.436 (+/-0.627) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.436 (+/-0.627) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.436 (+/-0.627) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.436 (+/-0.627) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.080 (+/-0.285) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.060 (+/-0.214) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.053 (+/-0.244) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.096 (+/-0.342) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.053 (+/-0.244) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.096 (+/-0.342) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.053 (+/-0.244) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.096 (+/-0.342) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.053 (+/-0.244) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.060 (+/-0.214) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.096 (+/-0.342) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.080 (+/-0.367) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
Detailed classification report:
The scores are computed on the test set.
precision recall f1-score support
0 0.67 0.80 0.73 5
1 0.80 0.67 0.73 6
avg / total 0.74 0.73 0.73 11
# Tuning hyper-parameters for recall
Best parameters found on training set:
{'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
Grid scores on training set:
0.180 (+/-0.480) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.160 (+/-0.405) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.420 (+/-0.491) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.420 (+/-0.491) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.420 (+/-0.491) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.420 (+/-0.491) for {'classify__C': 1, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.180 (+/-0.480) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.260 (+/-0.597) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.420 (+/-0.491) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.420 (+/-0.491) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.420 (+/-0.491) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.420 (+/-0.491) for {'classify__C': 2, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.180 (+/-0.480) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.340 (+/-0.569) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.420 (+/-0.491) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.420 (+/-0.491) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.420 (+/-0.491) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.420 (+/-0.491) for {'classify__C': 3, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.180 (+/-0.480) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.340 (+/-0.569) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.420 (+/-0.491) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.420 (+/-0.491) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.420 (+/-0.491) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.420 (+/-0.491) for {'classify__C': 4, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.180 (+/-0.480) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.340 (+/-0.569) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.420 (+/-0.491) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.420 (+/-0.491) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.420 (+/-0.491) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.420 (+/-0.491) for {'classify__C': 5, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.180 (+/-0.480) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 2}
0.080 (+/-0.367) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 3}
0.080 (+/-0.367) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 5}
0.420 (+/-0.749) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 10}
0.420 (+/-0.491) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 25}
0.420 (+/-0.491) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 26}
0.420 (+/-0.491) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 50}
0.420 (+/-0.491) for {'classify__C': 10, 'reduce_dim': PCA(copy=True, iterated_power=7, n_components=25, random_state=None,
svd_solver='auto', tol=0.0, whiten=False), 'reduce_dim__n_components': 75}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.080 (+/-0.285) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 1, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.080 (+/-0.285) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.080 (+/-0.367) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 2, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.160 (+/-0.569) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.080 (+/-0.367) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 3, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.160 (+/-0.569) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.080 (+/-0.367) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 4, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.160 (+/-0.569) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.080 (+/-0.367) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 5, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 2}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 3}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 5}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 10}
0.080 (+/-0.285) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 25}
0.160 (+/-0.569) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 26}
0.160 (+/-0.733) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 50}
0.000 (+/-0.000) for {'classify__C': 10, 'reduce_dim': SelectKBest(k=75, score_func=<function chi2 at 0x2b0717038ae8>), 'reduce_dim__k': 75}
Detailed classification report:
The scores are computed on the test set.
precision recall f1-score support
0 0.67 0.80 0.73 5
1 0.80 0.67 0.73 6
avg / total 0.74 0.73 0.73 11
[0 0 0 1 1 1 0 0 0 1 1]
[1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1]
Score: 0.67
......
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