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dev/_sources/auto_examples/applications/plot_model_complexity_influence.txt

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learning_rate='optimal', loss='modified_huber', n_iter=5, n_jobs=1,
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penalty='elasticnet', power_t=0.5, random_state=None, shuffle=True,
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verbose=0, warm_start=False)
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Complexity: 4454 | Hamming Loss (Misclassification Ratio): 0.2501 | Pred. Time: 0.026973s
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Complexity: 4454 | Hamming Loss (Misclassification Ratio): 0.2501 | Pred. Time: 0.025355s
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Benchmarking SGDClassifier(alpha=0.001, average=False, class_weight=None, epsilon=0.1,
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eta0=0.0, fit_intercept=True, l1_ratio=0.5, learning_rate='optimal',
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loss='modified_huber', n_iter=5, n_jobs=1, penalty='elasticnet',
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power_t=0.5, random_state=None, shuffle=True, verbose=0,
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warm_start=False)
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Complexity: 1624 | Hamming Loss (Misclassification Ratio): 0.2923 | Pred. Time: 0.020690s
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Complexity: 1624 | Hamming Loss (Misclassification Ratio): 0.2923 | Pred. Time: 0.019600s
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Benchmarking SGDClassifier(alpha=0.001, average=False, class_weight=None, epsilon=0.1,
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eta0=0.0, fit_intercept=True, l1_ratio=0.75,
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learning_rate='optimal', loss='modified_huber', n_iter=5, n_jobs=1,
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penalty='elasticnet', power_t=0.5, random_state=None, shuffle=True,
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verbose=0, warm_start=False)
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Complexity: 873 | Hamming Loss (Misclassification Ratio): 0.3191 | Pred. Time: 0.014987s
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Complexity: 873 | Hamming Loss (Misclassification Ratio): 0.3191 | Pred. Time: 0.015194s
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Benchmarking SGDClassifier(alpha=0.001, average=False, class_weight=None, epsilon=0.1,
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eta0=0.0, fit_intercept=True, l1_ratio=0.9, learning_rate='optimal',
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loss='modified_huber', n_iter=5, n_jobs=1, penalty='elasticnet',
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power_t=0.5, random_state=None, shuffle=True, verbose=0,
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warm_start=False)
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Complexity: 655 | Hamming Loss (Misclassification Ratio): 0.3252 | Pred. Time: 0.015665s
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Complexity: 655 | Hamming Loss (Misclassification Ratio): 0.3252 | Pred. Time: 0.013484s
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Benchmarking NuSVR(C=1000.0, cache_size=200, coef0=0.0, degree=3, gamma=3.0517578125e-05,
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kernel='rbf', max_iter=-1, nu=0.1, shrinking=True, tol=0.001,
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verbose=False)
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Complexity: 69 | MSE: 31.8133 | Pred. Time: 0.000360s
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Complexity: 69 | MSE: 31.8133 | Pred. Time: 0.000363s
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Benchmarking NuSVR(C=1000.0, cache_size=200, coef0=0.0, degree=3, gamma=3.0517578125e-05,
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kernel='rbf', max_iter=-1, nu=0.25, shrinking=True, tol=0.001,
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verbose=False)
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Complexity: 136 | MSE: 25.6140 | Pred. Time: 0.000646s
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Complexity: 136 | MSE: 25.6140 | Pred. Time: 0.000645s
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Benchmarking NuSVR(C=1000.0, cache_size=200, coef0=0.0, degree=3, gamma=3.0517578125e-05,
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kernel='rbf', max_iter=-1, nu=0.5, shrinking=True, tol=0.001,
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verbose=False)
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Complexity: 243 | MSE: 22.3315 | Pred. Time: 0.001108s
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Complexity: 243 | MSE: 22.3315 | Pred. Time: 0.001100s
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Benchmarking NuSVR(C=1000.0, cache_size=200, coef0=0.0, degree=3, gamma=3.0517578125e-05,
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kernel='rbf', max_iter=-1, nu=0.75, shrinking=True, tol=0.001,
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verbose=False)
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Complexity: 350 | MSE: 21.3679 | Pred. Time: 0.001562s
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Complexity: 350 | MSE: 21.3679 | Pred. Time: 0.001593s
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Benchmarking NuSVR(C=1000.0, cache_size=200, coef0=0.0, degree=3, gamma=3.0517578125e-05,
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kernel='rbf', max_iter=-1, nu=0.9, shrinking=True, tol=0.001,
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verbose=False)
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Complexity: 404 | MSE: 21.0915 | Pred. Time: 0.001797s
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Complexity: 404 | MSE: 21.0915 | Pred. Time: 0.001787s
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Benchmarking GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,
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learning_rate=0.1, loss='ls', max_depth=3, max_features=None,
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max_leaf_nodes=None, min_impurity_split=1e-07,
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min_samples_leaf=1, min_samples_split=2,
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min_weight_fraction_leaf=0.0, n_estimators=10, presort='auto',
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random_state=None, subsample=1.0, verbose=0, warm_start=False)
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Complexity: 10 | MSE: 28.9793 | Pred. Time: 0.000108s
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Complexity: 10 | MSE: 28.9793 | Pred. Time: 0.000109s
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Benchmarking GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,
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learning_rate=0.1, loss='ls', max_depth=3, max_features=None,
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max_leaf_nodes=None, min_impurity_split=1e-07,
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min_samples_leaf=1, min_samples_split=2,
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min_weight_fraction_leaf=0.0, n_estimators=50, presort='auto',
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random_state=None, subsample=1.0, verbose=0, warm_start=False)
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Complexity: 50 | MSE: 8.3398 | Pred. Time: 0.000193s
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Complexity: 50 | MSE: 8.3398 | Pred. Time: 0.000192s
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Benchmarking GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,
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learning_rate=0.1, loss='ls', max_depth=3, max_features=None,
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min_weight_fraction_leaf=0.0, n_estimators=200,
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presort='auto', random_state=None, subsample=1.0, verbose=0,
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warm_start=False)
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Complexity: 200 | MSE: 6.1836 | Pred. Time: 0.000445s
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Complexity: 200 | MSE: 6.1836 | Pred. Time: 0.000453s
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Benchmarking GradientBoostingRegressor(alpha=0.9, criterion='friedman_mse', init=None,
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learning_rate=0.1, loss='ls', max_depth=3, max_features=None,
@@ -315,10 +315,10 @@ main code
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min_weight_fraction_leaf=0.0, n_estimators=500,
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presort='auto', random_state=None, subsample=1.0, verbose=0,
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warm_start=False)
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Complexity: 500 | MSE: 6.3426 | Pred. Time: 0.001013s
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Complexity: 500 | MSE: 6.3426 | Pred. Time: 0.000968s
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dev/_sources/auto_examples/applications/plot_out_of_core_classification.txt

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Test set is 878 documents (108 positive)
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Passive-Aggressive classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.913 in 1.60s ( 602 docs/s)
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Perceptron classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.921 in 1.60s ( 601 docs/s)
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SGD classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.925 in 1.60s ( 599 docs/s)
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NB Multinomial classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.877 in 1.64s ( 587 docs/s)
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Passive-Aggressive classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.913 in 1.59s ( 604 docs/s)
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Perceptron classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.921 in 1.60s ( 602 docs/s)
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SGD classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.925 in 1.60s ( 601 docs/s)
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NB Multinomial classifier : 962 train docs ( 132 positive) 878 test docs ( 108 positive) accuracy: 0.877 in 1.63s ( 588 docs/s)
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Passive-Aggressive classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.946 in 4.73s ( 826 docs/s)
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Perceptron classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.926 in 4.74s ( 825 docs/s)
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SGD classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.945 in 4.74s ( 825 docs/s)
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NB Multinomial classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.885 in 4.77s ( 819 docs/s)
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Passive-Aggressive classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.946 in 4.71s ( 830 docs/s)
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Perceptron classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.926 in 4.71s ( 829 docs/s)
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SGD classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.945 in 4.72s ( 829 docs/s)
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NB Multinomial classifier : 3911 train docs ( 517 positive) 878 test docs ( 108 positive) accuracy: 0.885 in 4.75s ( 823 docs/s)
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Passive-Aggressive classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 7.74s ( 881 docs/s)
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Perceptron classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.949 in 7.74s ( 881 docs/s)
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SGD classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.938 in 7.75s ( 880 docs/s)
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NB Multinomial classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.899 in 7.78s ( 876 docs/s)
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Passive-Aggressive classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 7.72s ( 883 docs/s)
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Perceptron classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.949 in 7.73s ( 882 docs/s)
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SGD classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.938 in 7.73s ( 882 docs/s)
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NB Multinomial classifier : 6821 train docs ( 891 positive) 878 test docs ( 108 positive) accuracy: 0.899 in 7.76s ( 878 docs/s)
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Passive-Aggressive classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.964 in 10.87s ( 898 docs/s)
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Perceptron classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.950 in 10.87s ( 897 docs/s)
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SGD classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.958 in 10.87s ( 897 docs/s)
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NB Multinomial classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.909 in 10.91s ( 894 docs/s)
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Passive-Aggressive classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.964 in 10.73s ( 909 docs/s)
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Perceptron classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.950 in 10.73s ( 909 docs/s)
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SGD classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.958 in 10.73s ( 909 docs/s)
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NB Multinomial classifier : 9759 train docs ( 1276 positive) 878 test docs ( 108 positive) accuracy: 0.909 in 10.77s ( 906 docs/s)
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Passive-Aggressive classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 13.67s ( 854 docs/s)
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Perceptron classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 13.67s ( 854 docs/s)
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SGD classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 13.68s ( 853 docs/s)
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NB Multinomial classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.916 in 13.71s ( 851 docs/s)
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Passive-Aggressive classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 13.52s ( 863 docs/s)
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Perceptron classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 13.52s ( 863 docs/s)
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SGD classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.951 in 13.53s ( 863 docs/s)
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NB Multinomial classifier : 11680 train docs ( 1499 positive) 878 test docs ( 108 positive) accuracy: 0.916 in 13.56s ( 861 docs/s)
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Passive-Aggressive classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.966 in 16.81s ( 870 docs/s)
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Perceptron classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.956 in 16.81s ( 870 docs/s)
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SGD classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.954 in 16.81s ( 869 docs/s)
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NB Multinomial classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.926 in 16.85s ( 868 docs/s)
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Passive-Aggressive classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.966 in 16.61s ( 880 docs/s)
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Perceptron classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.956 in 16.61s ( 880 docs/s)
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SGD classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.954 in 16.61s ( 880 docs/s)
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NB Multinomial classifier : 14625 train docs ( 1865 positive) 878 test docs ( 108 positive) accuracy: 0.926 in 16.65s ( 878 docs/s)
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Passive-Aggressive classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.954 in 19.78s ( 877 docs/s)
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Perceptron classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.957 in 19.78s ( 877 docs/s)
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SGD classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.949 in 19.78s ( 877 docs/s)
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NB Multinomial classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.932 in 19.82s ( 875 docs/s)
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Passive-Aggressive classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.954 in 19.57s ( 887 docs/s)
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Perceptron classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.957 in 19.57s ( 887 docs/s)
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SGD classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.949 in 19.57s ( 886 docs/s)
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NB Multinomial classifier : 17360 train docs ( 2179 positive) 878 test docs ( 108 positive) accuracy: 0.932 in 19.61s ( 885 docs/s)
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dev/_sources/auto_examples/applications/plot_outlier_detection_housing.txt

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dev/_sources/auto_examples/applications/plot_prediction_latency.txt

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dev/_sources/auto_examples/applications/plot_species_distribution_modeling.txt

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dev/_sources/auto_examples/applications/plot_stock_market.txt

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dev/_sources/auto_examples/applications/plot_tomography_l1_reconstruction.txt

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dev/_sources/auto_examples/bicluster/plot_spectral_biclustering.txt

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dev/_sources/auto_examples/calibration/plot_calibration.txt

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dev/_sources/auto_examples/calibration/plot_calibration_curve.txt

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dev/_sources/auto_examples/calibration/plot_calibration_multiclass.txt

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dev/_sources/auto_examples/calibration/plot_compare_calibration.txt

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dev/_sources/auto_examples/classification/plot_classification_probability.txt

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dev/_sources/auto_examples/classification/plot_classifier_comparison.txt

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dev/_sources/auto_examples/classification/plot_digits_classification.txt

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dev/_sources/auto_examples/classification/plot_lda.txt

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dev/_sources/auto_examples/cluster/plot_adjusted_for_chance_measures.txt

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Computing adjusted_rand_score for 10 values of n_clusters and n_samples=100
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Computing v_measure_score for 10 values of n_clusters and n_samples=100
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Computing adjusted_mutual_info_score for 10 values of n_clusters and n_samples=100
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Computing mutual_info_score for 10 values of n_clusters and n_samples=100
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Computing adjusted_rand_score for 10 values of n_clusters and n_samples=1000
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Computing v_measure_score for 10 values of n_clusters and n_samples=1000
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Computing adjusted_mutual_info_score for 10 values of n_clusters and n_samples=1000
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Computing mutual_info_score for 10 values of n_clusters and n_samples=1000
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@@ -171,7 +171,7 @@ value of k on various overlapping sub-samples of the dataset.
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plt.legend(plots, names)
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dev/_sources/auto_examples/cluster/plot_affinity_propagation.txt

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dev/_sources/auto_examples/cluster/plot_agglomerative_clustering.txt

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plt.show()
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