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 |  موضوع: كتاب Scikit-learn User Guide السبت 01 مايو 2021, 1:11 am | |
| 
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أحضرت لكم كتاب
Scikit-learn User Guide
Scikit-learn Developers
و المحتوى كما يلي :
CONTENTS
1 Welcome to scikit-learn 1
1.1 Installing scikit-learn . 1
1.2 Frequently Asked Questions . 2
1.3 Support 7
1.4 Related Projects . 8
1.5 About us . 10
1.6 Who is using scikit-learn? 14
1.7 Release history 21
2 scikit-learn Tutorials 91
2.1 An introduction to machine learning with scikit-learn 91
2.2 A tutorial on statistical-learning for scientific data processing . 97
2.3 Working With Text Data . 124
2.4 Choosing the right estimator . 131
2.5 External Resources, Videos and Talks 131
3 User Guide 133
3.1 Supervised learning . 133
3.2 Unsupervised learning 269
3.3 Model selection and evaluation . 352
3.4 Dataset transformations . 480
3.5 Dataset loading utilities . 516
3.6 Strategies to scale computationally: bigger data . 542
3.7 Computational Performance . 545
4 General examples 553
4.1 Plotting Cross-Validated Predictions . 553
4.2 Isotonic Regression . 554
4.3 Concatenating multiple feature extraction methods . 556
4.4 Pipelining: chaining a PCA and a logistic regression 557
4.5 Selecting dimensionality reduction with Pipeline and GridSearchCV 559
4.6 Imputing missing values before building an estimator 561
4.7 Face completion with a multi-output estimators . 563
4.8 Multilabel classification . 565
4.9 The Johnson-Lindenstrauss bound for embedding with random projections 568
4.10 Comparison of kernel ridge regression and SVR 573
4.11 Feature Union with Heterogeneous Data Sources 577
4.12 Explicit feature map approximation for RBF kernels 580
5 Examples based on real world datasets 585
5.1 Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation . 585
i5.2 Outlier detection on a real data set 587
5.3 Compressive sensing: tomography reconstruction with L1 prior (Lasso) 589
5.4 Faces recognition example using eigenfaces and SVMs . 592
5.5 Model Complexity Influence . 595
5.6 Species distribution modeling 600
5.7 Visualizing the stock market structure 605
5.8 Wikipedia principal eigenvector . 610
5.9 Libsvm GUI . 614
5.10 Prediction Latency 620
5.11 Out-of-core classification of text documents . 626
6 Biclustering 637
6.1 A demo of the Spectral Co-Clustering algorithm 637
6.2 A demo of the Spectral Biclustering algorithm . 639
6.3 Biclustering documents with the Spectral Co-clustering algorithm . 642
7 Calibration 647
7.1 Comparison of Calibration of Classifiers 647
7.2 Probability Calibration curves 650
7.3 Probability calibration of classifiers . 654
7.4 Probability Calibration for 3-class classification . 656
8 Classification 661
8.1 Recognizing hand-written digits . 661
8.2 Normal and Shrinkage Linear Discriminant Analysis for classification . 663
8.3 Plot classification probability 665
8.4 Classifier comparison 668
8.5 Linear and Quadratic Discriminant Analysis with confidence ellipsoid . 671
9 Clustering 675
9.1 A demo of the mean-shift clustering algorithm . 675
9.2 Feature agglomeration 677
9.3 Demonstration of k-means assumptions . 678
9.4 A demo of structured Ward hierarchical clustering on a raccoon face image 680
9.5 Online learning of a dictionary of parts of faces . 682
9.6 Demo of affinity propagation clustering algorithm . 685
9.7 Hierarchical clustering: structured vs unstructured ward 687
9.8 Agglomerative clustering with and without structure 690
9.9 K-means Clustering . 692
9.10 Segmenting the picture of a raccoon face in regions . 694
9.11 Demo of DBSCAN clustering algorithm 697
9.12 Spectral clustering for image segmentation . 699
9.13 Vector Quantization Example 702
9.14 Various Agglomerative Clustering on a 2D embedding of digits 704
9.15 Color Quantization using K-Means . 706
9.16 Agglomerative clustering with different metrics . 709
9.17 Comparison of the K-Means and MiniBatchKMeans clustering algorithms 713
9.18 Feature agglomeration vs. univariate selection . 715
9.19 Compare BIRCH and MiniBatchKMeans 718
9.20 Empirical evaluation of the impact of k-means initialization 720
9.21 Adjustment for chance in clustering performance evaluation 723
9.22 A demo of K-Means clustering on the handwritten digits data . 726
9.23 Comparing different clustering algorithms on toy datasets . 729
9.24 Selecting the number of clusters with silhouette analysis on KMeans clustering 732
ii10 Covariance estimation 737
10.1 Ledoit-Wolf vs OAS estimation . 737
10.2 Sparse inverse covariance estimation 739
10.3 Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihood . 742
10.4 Outlier detection with several methods 745
10.5 Robust covariance estimation and Mahalanobis distances relevance 747
10.6 Robust vs Empirical covariance estimate 750
11 Cross decomposition 755
11.1 Compare cross decomposition methods . 755
12 Dataset examples 761
12.1 The Digit Dataset . 761
12.2 The Iris Dataset 762
12.3 Plot randomly generated classification dataset 763
12.4 Plot randomly generated multilabel dataset . 765
13 Decomposition 769
13.1 PCA example with Iris Data-set . 769
13.2 Incremental PCA . 770
13.3 Comparison of LDA and PCA 2D projection of Iris dataset . 772
13.4 Blind source separation using FastICA . 774
13.5 FastICA on 2D point clouds . 776
13.6 Kernel PCA 778
13.7 Principal components analysis (PCA) 780
13.8 Model selection with Probabilistic PCA and Factor Analysis (FA) . 782
13.9 Sparse coding with a precomputed dictionary 785
13.10 Faces dataset decompositions 787
13.11 Image denoising using dictionary learning 793
14 Ensemble methods 799
14.1 Decision Tree Regression with AdaBoost 799
14.2 Pixel importances with a parallel forest of trees . 800
14.3 IsolationForest example . 802
14.4 Feature importances with forests of trees 804
14.5 Plot the decision boundaries of a VotingClassifier 806
14.6 Comparing random forests and the multi-output meta estimator 808
14.7 Gradient Boosting regression 810
14.8 Prediction Intervals for Gradient Boosting Regression . 813
14.9 Plot class probabilities calculated by the VotingClassifier 815
14.10 Gradient Boosting regularization 817
14.11 OOB Errors for Random Forests . 819
14.12 Two-class AdaBoost . 821
14.13 Hashing feature transformation using Totally Random Trees 824
14.14 Partial Dependence Plots . 826
14.15 Discrete versus Real AdaBoost . 829
14.16 Multi-class AdaBoosted Decision Trees . 831
14.17 Feature transformations with ensembles of trees 833
14.18 Gradient Boosting Out-of-Bag estimates 836
14.19 Single estimator versus bagging: bias-variance decomposition . 839
14.20 Plot the decision surfaces of ensembles of trees on the iris dataset . 844
15 Tutorial exercises 849
15.1 Digits Classification Exercise 849
15.2 Cross-validation on Digits Dataset Exercise . 849
iii15.3 SVM Exercise 851
15.4 Cross-validation on diabetes Dataset Exercise 853
16 Feature Selection 857
16.1 Pipeline Anova SVM . 857
16.2 Recursive feature elimination 857
16.3 Comparison of F-test and mutual information 859
16.4 Recursive feature elimination with cross-validation . 860
16.5 Feature selection using SelectFromModel and LassoCV 862
16.6 Univariate Feature Selection . 863
16.7 Test with permutations the significance of a classification score 867
17 Gaussian Process for Machine Learning 871
17.1 Illustration of Gaussian process classification (GPC) on the XOR dataset . 871
17.2 Gaussian process classification (GPC) on iris dataset 872
17.3 Comparison of kernel ridge and Gaussian process regression 874
17.4 Gaussian process regression (GPR) on Mauna Loa CO2 data 877
17.5 Illustration of prior and posterior Gaussian process for different kernels 880
17.6 Iso-probability lines for Gaussian Processes classification (GPC) 883
17.7 Probabilistic predictions with Gaussian process classification (GPC) 886
17.8 Gaussian process regression (GPR) with noise-level estimation 889
17.9 Gaussian Processes regression: basic introductory example . 891
18 Generalized Linear Models 895
18.1 Lasso path using LARS . 895
18.2 Plot Ridge coefficients as a function of the regularization 896
18.3 Path with L1- Logistic Regression 898
18.4 SGD: Maximum margin separating hyperplane . 900
18.5 SGD: convex loss functions . 902
18.6 Plot Ridge coefficients as a function of the L2 regularization 903
18.7 Ordinary Least Squares and Ridge Regression Variance 905
18.8 Logistic function . 906
18.9 Polynomial interpolation . 908
18.10 Linear Regression Example . 910
18.11 Logistic Regression 3-class Classifier 912
18.12 SGD: Weighted samples . 914
18.13 Lasso on dense and sparse data . 915
18.14 Lasso and Elastic Net for Sparse Signals 916
18.15 Sparsity Example: Fitting only features 1 and 2 . 919
18.16 Joint feature selection with multi-task Lasso 920
18.17 Comparing various online solvers 922
18.18 Robust linear model estimation using RANSAC 924
18.19 HuberRegressor vs Ridge on dataset with strong outliers 926
18.20 SGD: Penalties 928
18.21 Bayesian Ridge Regression . 930
18.22 Automatic Relevance Determination Regression (ARD) 933
18.23 Orthogonal Matching Pursuit 935
18.24 Plot multi-class SGD on the iris dataset . 939
18.25 Theil-Sen Regression . 941
18.26 L1 Penalty and Sparsity in Logistic Regression . 944
18.27 Plot multinomial and One-vs-Rest Logistic Regression . 947
18.28 Robust linear estimator fitting 949
18.29 Lasso and Elastic Net 951
18.30 Lasso model selection: Cross-Validation / AIC / BIC 954
iv18.31 Sparse recovery: feature selection for sparse linear models . 958
19 Manifold learning 963
19.1 Swiss Roll reduction with LLE . 963
19.2 Multi-dimensional scaling 964
19.3 Comparison of Manifold Learning methods . 967
19.4 Manifold Learning methods on a severed sphere 969
19.5 Manifold learning on handwritten digits: Locally Linear Embedding, Isomap.. . 973
20 Gaussian Mixture Models 981
20.1 Density Estimation for a Gaussian mixture . 981
20.2 Gaussian Mixture Model Ellipsoids . 982
20.3 Gaussian Mixture Model Selection . 984
20.4 GMM covariances 987
20.5 Gaussian Mixture Model Sine Curve 990
20.6 Concentration Prior Type Analysis of Variation Bayesian Gaussian Mixture 994
21 Model Selection 997
21.1 Plotting Validation Curves 997
21.2 Underfitting vs. Overfitting . 998
21.3 Train error vs Test error . 1000
21.4 Receiver Operating Characteristic (ROC) with cross validation . 1002
21.5 Parameter estimation using grid search with cross-validation 1004
21.6 Confusion matrix . 1006
21.7 Comparing randomized search and grid search for hyperparameter estimation . 1009
21.8 Nested versus non-nested cross-validation 1010
21.9 Sample pipeline for text feature extraction and evaluation . 1013
21.10 Precision-Recall . 1015
21.11 Receiver Operating Characteristic (ROC) 1018
21.12 Plotting Learning Curves . 1022
22 Nearest Neighbors 1027
22.1 Nearest Neighbors regression 1027
22.2 Nearest Neighbors Classification 1028
22.3 Nearest Centroid Classification . 1030
22.4 Kernel Density Estimation 1032
22.5 Kernel Density Estimate of Species Distributions 1034
22.6 Simple 1D Kernel Density Estimation 1037
22.7 Hyper-parameters of Approximate Nearest Neighbors . 1040
22.8 Scalability of Approximate Nearest Neighbors . 1043
23 Neural Networks 1047
23.1 Visualization of MLP weights on MNIST 1047
23.2 Restricted Boltzmann Machine features for digit classification . 1049
23.3 Compare Stochastic learning strategies for MLPClassifier . 1053
23.4 Varying regularization in Multi-layer Perceptron 1057
24 Preprocessing 1061
24.1 Using FunctionTransformer to select columns 1061
24.2 Robust Scaling on Toy Data . 1063
25 Semi Supervised Classification 1065
25.1 Label Propagation learning a complex structure . 1065
25.2 Label Propagation digits: Demonstrating performance . 1066
25.3 Decision boundary of label propagation versus SVM on the Iris dataset 1069
v25.4 Label Propagation digits active learning . 1071
26 Support Vector Machines 1077
26.1 Support Vector Regression (SVR) using linear and non-linear kernels . 1077
26.2 Non-linear SVM . 1078
26.3 SVM: Maximum margin separating hyperplane . 1080
26.4 SVM: Separating hyperplane for unbalanced classes 1081
26.5 SVM-Anova: SVM with univariate feature selection 1083
26.6 SVM with custom kernel . 1085
26.7 SVM: Weighted samples . 1086
26.8 SVM-Kernels . 1088
26.9 SVM Margins Example . 1090
26.10 Plot different SVM classifiers in the iris dataset . 1092
26.11 One-class SVM with non-linear kernel (RBF) 1094
26.12 Scaling the regularization parameter for SVCs . 1096
26.13 RBF SVM parameters 1099
27 Working with text documents 1105
27.1 FeatureHasher and DictVectorizer Comparison . 1105
27.2 Classification of text documents: using a MLComp dataset . 1107
27.3 Clustering text documents using k-means 1109
27.4 Classification of text documents using sparse features . 1113
28 Decision Trees 1119
28.1 Decision Tree Regression 1119
28.2 Multi-output Decision Tree Regression . 1121
28.3 Plot the decision surface of a decision tree on the iris dataset 1122
28.4 Understanding the decision tree structure 1124
29 API Reference 1129
29.1 sklearn.base: Base classes and utility functions 1129
29.2 sklearn.cluster: Clustering 1133
29.3 sklearn.cluster.bicluster: Biclustering . 1169
29.4 sklearn.covariance: Covariance Estimators . 1174
29.5 sklearn.model_selection: Model Selection 1203
29.6 sklearn.datasets: Datasets 1249
29.7 sklearn.decomposition: Matrix Decomposition 1295
29.8 sklearn.dummy: Dummy estimators . 1349
29.9 sklearn.ensemble: Ensemble Methods 1354
29.10 sklearn.exceptions: Exceptions and warnings . 1383
29.11 sklearn.feature_extraction: Feature Extraction . 1386
29.12 sklearn.feature_selection: Feature Selection 1413
29.13 sklearn.gaussian_process: Gaussian Processes 1444
29.14 sklearn.isotonic: Isotonic regression 1476
29.15 sklearn.kernel_approximation Kernel Approximation . 1481
29.16 sklearn.kernel_ridge Kernel Ridge Regression 1489
29.17 sklearn.discriminant_analysis: Discriminant Analysis 1492
29.18 sklearn.linear_model: Generalized Linear Models . 1501
29.19 sklearn.manifold: Manifold Learning 1606
29.20 sklearn.metrics: Metrics . 1622
29.21 sklearn.mixture: Gaussian Mixture Models . 1686
29.22 sklearn.multiclass: Multiclass and multilabel classification 1697
29.23 sklearn.multioutput: Multioutput regression and classification 1705
29.24 sklearn.naive_bayes: Naive Bayes . 1709
29.25 sklearn.neighbors: Nearest Neighbors 1719
vi29.26 sklearn.neural_network: Neural network models . 1770
29.27 sklearn.calibration: Probability Calibration 1783
29.28 sklearn.cross_decomposition: Cross decomposition 1787
29.29 sklearn.pipeline: Pipeline 1801
29.30 sklearn.preprocessing: Preprocessing and Normalization . 1808
29.31 sklearn.random_projection: Random projection . 1845
29.32 sklearn.semi_supervised Semi-Supervised Learning . 1851
29.33 sklearn.svm: Support Vector Machines . 1857
29.34 sklearn.tree: Decision Trees 1890
29.35 sklearn.utils: Utilities . 1912
29.36 Recently deprecated . 1915
30 Developer’s Guide 1973
30.1 Contributing . 1973
30.2 Developers’ Tips for Debugging . 1987
30.3 Utilities for Developers . 1988
30.4 How to optimize for speed 1992
30.5 Advanced installation instructions 1999
30.6 Maintainer / core-developer information . 2005
Bibliography 2007
Index
INDEX
Symbols
__init__() (sklearn.base.BaseEstimator method), 1129
__init__() (sklearn.base.ClassifierMixin method), 1130
__init__() (sklearn.base.ClusterMixin method), 1131
__init__() (sklearn.base.RegressorMixin method), 1131
__init__() (sklearn.base.TransformerMixin method),
1132
__init__() (sklearn.calibration.CalibratedClassifierCV
method), 1784
__init__() (sklearn.cluster.AffinityPropagation method),
1134
__init__() (sklearn.cluster.AgglomerativeClustering
method), 1137
__init__() (sklearn.cluster.Birch method), 1139
__init__() (sklearn.cluster.DBSCAN method), 1142
__init__() (sklearn.cluster.FeatureAgglomeration
method), 1145
__init__() (sklearn.cluster.KMeans method), 1150
__init__() (sklearn.cluster.MeanShift method), 1156
__init__() (sklearn.cluster.MiniBatchKMeans method),
1153
__init__() (sklearn.cluster.SpectralClustering method),
1159
__init__() (sklearn.cluster.bicluster.SpectralBiclustering
method), 1171
__init__() (sklearn.cluster.bicluster.SpectralCoclustering
method), 1173
__init__() (sklearn.covariance.EllipticEnvelope method),
1179
__init__() (sklearn.covariance.EmpiricalCovariance
method), 1176
__init__() (sklearn.covariance.GraphLasso method),
1182
__init__() (sklearn.covariance.GraphLassoCV method),
1186
__init__() (sklearn.covariance.LedoitWolf method), 1188
__init__() (sklearn.covariance.MinCovDet method), 1192
__init__() (sklearn.covariance.OAS method), 1195
__init__() (sklearn.covariance.ShrunkCovariance
method), 1198
__init__() (sklearn.cross_decomposition.CCA method),
1797
__init__() (sklearn.cross_decomposition.PLSCanonical
method), 1794
__init__() (sklearn.cross_decomposition.PLSRegression
method), 1789
__init__() (sklearn.cross_decomposition.PLSSVD
method), 1800
__init__() (sklearn.cross_validation.LabelShuffleSplit
method), 1940
__init__() (sklearn.decomposition.DictionaryLearning
method), 1334
__init__() (sklearn.decomposition.FactorAnalysis
method), 1314
__init__() (sklearn.decomposition.FastICA method),
1317
__init__() (sklearn.decomposition.IncrementalPCA
method), 1303
__init__() (sklearn.decomposition.KernelPCA method),
1311
__init__() (sklearn.decomposition.LatentDirichletAllocation
method), 1341
__init__() (sklearn.decomposition.MiniBatchDictionaryLearning
method), 1337
__init__() (sklearn.decomposition.MiniBatchSparsePCA
method), 1329
__init__() (sklearn.decomposition.NMF method), 1324
__init__() (sklearn.decomposition.PCA method), 1298
__init__() (sklearn.decomposition.ProjectedGradientNMF
method), 1308
__init__() (sklearn.decomposition.RandomizedPCA
method), 1945
__init__() (sklearn.decomposition.SparseCoder method),
1331
__init__() (sklearn.decomposition.SparsePCA method),
1326
__init__() (sklearn.decomposition.TruncatedSVD
method), 1319
__init__() (sklearn.discriminant_analysis.LinearDiscriminantAnalysis
method), 1495
__init__() (sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis
method), 1499
__init__() (sklearn.dummy.DummyClassifier method),
1350
2015scikit-learn user guide, Release 0.18.2
__init__() (sklearn.dummy.DummyRegressor method),
1353
__init__() (sklearn.ensemble.AdaBoostClassifier
method), 1356
__init__() (sklearn.ensemble.AdaBoostRegressor
method), 1361
__init__() (sklearn.ensemble.BaggingClassifier method),
1365
__init__() (sklearn.ensemble.BaggingRegressor method),
1369
__init__() (sklearn.ensemble.ExtraTreesClassifier
method), 430
__init__() (sklearn.ensemble.ExtraTreesRegressor
method), 436
__init__() (sklearn.ensemble.GradientBoostingClassifier
method), 442
__init__() (sklearn.ensemble.GradientBoostingRegressor
method), 449
__init__() (sklearn.ensemble.IsolationForest method),
1372
__init__() (sklearn.ensemble.RandomForestClassifier
method), 418
__init__() (sklearn.ensemble.RandomForestRegressor
method), 424
__init__() (sklearn.ensemble.RandomTreesEmbedding
method), 1375
__init__() (sklearn.ensemble.VotingClassifier method),
1378
__init__() (sklearn.feature_extraction.DictVectorizer
method), 1387
__init__() (sklearn.feature_extraction.FeatureHasher
method), 1391
__init__() (sklearn.feature_extraction.image.PatchExtractor
method), 1395
__init__() (sklearn.feature_extraction.text.CountVectorizer
method), 1399
__init__() (sklearn.feature_extraction.text.HashingVectorizer
method), 1404
__init__() (sklearn.feature_extraction.text.TfidfTransformer
method), 1406
__init__() (sklearn.feature_extraction.text.TfidfVectorizer
method), 1411
__init__() (sklearn.feature_selection.GenericUnivariateSelect
method), 1414
__init__() (sklearn.feature_selection.RFE method), 1432
__init__() (sklearn.feature_selection.RFECV method),
1436
__init__() (sklearn.feature_selection.SelectFdr method),
1424
__init__() (sklearn.feature_selection.SelectFpr method),
1422
__init__() (sklearn.feature_selection.SelectFromModel
method), 1426
__init__() (sklearn.feature_selection.SelectFwe method),
1429
__init__() (sklearn.feature_selection.SelectKBest
method), 1419
__init__() (sklearn.feature_selection.SelectPercentile
method), 1416
__init__() (sklearn.feature_selection.VarianceThreshold
method), 1438
__init__() (sklearn.gaussian_process.GaussianProcess
method), 1949
__init__() (sklearn.gaussian_process.GaussianProcessClassifier
method), 1451
__init__() (sklearn.gaussian_process.GaussianProcessRegressor
method), 1447
__init__() (sklearn.gaussian_process.kernels.CompoundKernel
method), 1474
__init__() (sklearn.gaussian_process.kernels.ConstantKernel
method), 1460
__init__() (sklearn.gaussian_process.kernels.DotProduct
method), 1471
__init__() (sklearn.gaussian_process.kernels.ExpSineSquared
method), 1469
__init__() (sklearn.gaussian_process.kernels.Exponentiation
method), 1458
__init__() (sklearn.gaussian_process.kernels.Hyperparameter
method), 1476
__init__() (sklearn.gaussian_process.kernels.Kernel
method), 1454
__init__() (sklearn.gaussian_process.kernels.Matern
method), 1465
__init__() (sklearn.gaussian_process.kernels.PairwiseKernel
method), 1473
__init__() (sklearn.gaussian_process.kernels.Product
method), 1457
__init__() (sklearn.gaussian_process.kernels.RBF
method), 1463
__init__() (sklearn.gaussian_process.kernels.RationalQuadratic
method), 1467
__init__() (sklearn.gaussian_process.kernels.Sum
method), 1455
__init__() (sklearn.gaussian_process.kernels.WhiteKernel
method), 1462
__init__() (sklearn.grid_search.GridSearchCV method),
1926
__init__() (sklearn.grid_search.RandomizedSearchCV
method), 1931
__init__() (sklearn.isotonic.IsotonicRegression method),
1478
__init__() (sklearn.kernel_approximation.AdditiveChi2Sampler
method), 1482
__init__() (sklearn.kernel_approximation.Nystroem
method), 1485
__init__() (sklearn.kernel_approximation.RBFSampler
method), 1486
2016 Indexscikit-learn user guide, Release 0.18.2
__init__() (sklearn.kernel_approximation.SkewedChi2Sampler
method), 1488
__init__() (sklearn.kernel_ridge.KernelRidge method),
1491
__init__() (sklearn.lda.LDA method), 1916
__init__() (sklearn.linear_model.ARDRegression
method), 1504
__init__() (sklearn.linear_model.BayesianRidge
method), 1507
__init__() (sklearn.linear_model.ElasticNet method),
1511
__init__() (sklearn.linear_model.ElasticNetCV method),
367
__init__() (sklearn.linear_model.HuberRegressor
method), 1515
__init__() (sklearn.linear_model.Lars method), 1519
__init__() (sklearn.linear_model.LarsCV method), 372
__init__() (sklearn.linear_model.Lasso method), 1522
__init__() (sklearn.linear_model.LassoCV method), 376
__init__() (sklearn.linear_model.LassoLars method),
1528
__init__() (sklearn.linear_model.LassoLarsCV method),
382
__init__() (sklearn.linear_model.LassoLarsIC method),
413
__init__() (sklearn.linear_model.LinearRegression
method), 1530
__init__() (sklearn.linear_model.LogisticRegression
method), 1535
__init__() (sklearn.linear_model.LogisticRegressionCV
method), 386
__init__() (sklearn.linear_model.MultiTaskElasticNet
method), 1546
__init__() (sklearn.linear_model.MultiTaskElasticNetCV
method), 392
__init__() (sklearn.linear_model.MultiTaskLasso
method), 1540
__init__() (sklearn.linear_model.MultiTaskLassoCV
method), 398
__init__() (sklearn.linear_model.OrthogonalMatchingPursuit
method), 1550
__init__() (sklearn.linear_model.OrthogonalMatchingPursuitCV
method), 403
__init__() (sklearn.linear_model.PassiveAggressiveClassifier
method), 1553
__init__() (sklearn.linear_model.PassiveAggressiveRegressor
method), 1557
__init__() (sklearn.linear_model.Perceptron method),
1560
__init__() (sklearn.linear_model.RANSACRegressor
method), 1572
__init__() (sklearn.linear_model.RandomizedLasso
method), 1566
__init__() (sklearn.linear_model.RandomizedLogisticRegression
method), 1569
__init__() (sklearn.linear_model.Ridge method), 1576
__init__() (sklearn.linear_model.RidgeCV method), 406
__init__() (sklearn.linear_model.RidgeClassifier
method), 1579
__init__() (sklearn.linear_model.RidgeClassifierCV
method), 409
__init__() (sklearn.linear_model.SGDClassifier method),
1584
__init__() (sklearn.linear_model.SGDRegressor method),
1590
__init__() (sklearn.linear_model.TheilSenRegressor
method), 1594
__init__() (sklearn.manifold.Isomap method), 1610
__init__() (sklearn.manifold.LocallyLinearEmbedding
method), 1608
__init__() (sklearn.manifold.MDS method), 1613
__init__() (sklearn.manifold.SpectralEmbedding
method), 1615
__init__() (sklearn.manifold.TSNE method), 1619
__init__() (sklearn.mixture.BayesianGaussianMixture
method), 1695
__init__() (sklearn.mixture.DPGMM method), 1954
__init__() (sklearn.mixture.GMM method), 1952
__init__() (sklearn.mixture.GaussianMixture method),
1689
__init__() (sklearn.mixture.VBGMM method), 1958
__init__() (sklearn.model_selection.GridSearchCV
method), 1231
__init__() (sklearn.model_selection.GroupKFold
method), 1207
__init__() (sklearn.model_selection.GroupShuffleSplit
method), 1218
__init__() (sklearn.model_selection.KFold method), 1205
__init__() (sklearn.model_selection.LeaveOneGroupOut
method), 1210
__init__() (sklearn.model_selection.LeaveOneOut
method), 1213
__init__() (sklearn.model_selection.LeavePGroupsOut
method), 1212
__init__() (sklearn.model_selection.LeavePOut method),
1215
__init__() (sklearn.model_selection.PredefinedSplit
method), 1222
__init__() (sklearn.model_selection.RandomizedSearchCV
method), 1236
__init__() (sklearn.model_selection.ShuffleSplit
method), 1217
__init__() (sklearn.model_selection.StratifiedKFold
method), 1208
__init__() (sklearn.model_selection.StratifiedShuffleSplit
method), 1220
Index 2017scikit-learn user guide, Release 0.18.2
__init__() (sklearn.model_selection.TimeSeriesSplit
method), 1223
__init__() (sklearn.multiclass.OneVsOneClassifier
method), 1701
__init__() (sklearn.multiclass.OneVsRestClassifier
method), 1699
__init__() (sklearn.multiclass.OutputCodeClassifier
method), 1704
__init__() (sklearn.multioutput.MultiOutputClassifier
method), 1708
__init__() (sklearn.multioutput.MultiOutputRegressor
method), 1706
__init__() (sklearn.naive_bayes.BernoulliNB method),
1717
__init__() (sklearn.naive_bayes.GaussianNB method),
1710
__init__() (sklearn.naive_bayes.MultinomialNB method),
1714
__init__() (sklearn.neighbors.BallTree method), 1749
__init__() (sklearn.neighbors.DistanceMetric method),
1764
__init__() (sklearn.neighbors.KDTree method), 1754
__init__() (sklearn.neighbors.KNeighborsClassifier
method), 1728
__init__() (sklearn.neighbors.KNeighborsRegressor
method), 1737
__init__() (sklearn.neighbors.KernelDensity method),
1766
__init__() (sklearn.neighbors.LSHForest method), 1759
__init__() (sklearn.neighbors.NearestCentroid method),
1745
__init__() (sklearn.neighbors.NearestNeighbors method),
1722
__init__() (sklearn.neighbors.RadiusNeighborsClassifier
method), 1732
__init__() (sklearn.neighbors.RadiusNeighborsRegressor
method), 1741
__init__() (sklearn.neural_network.BernoulliRBM
method), 1771
__init__() (sklearn.neural_network.MLPClassifier
method), 1776
__init__() (sklearn.neural_network.MLPRegressor
method), 1782
__init__() (sklearn.pipeline.FeatureUnion method), 1806
__init__() (sklearn.pipeline.Pipeline method), 1802
__init__() (sklearn.preprocessing.Binarizer method),
1809
__init__() (sklearn.preprocessing.FunctionTransformer
method), 1811
__init__() (sklearn.preprocessing.Imputer method), 1813
__init__() (sklearn.preprocessing.KernelCenterer
method), 1814
__init__() (sklearn.preprocessing.LabelBinarizer
method), 1817
__init__() (sklearn.preprocessing.LabelEncoder method),
1820
__init__() (sklearn.preprocessing.MaxAbsScaler
method), 1823
__init__() (sklearn.preprocessing.MinMaxScaler
method), 1826
__init__() (sklearn.preprocessing.MultiLabelBinarizer
method), 1821
__init__() (sklearn.preprocessing.Normalizer method),
1828
__init__() (sklearn.preprocessing.OneHotEncoder
method), 1830
__init__() (sklearn.preprocessing.PolynomialFeatures
method), 1833
__init__() (sklearn.preprocessing.RobustScaler method),
1835
__init__() (sklearn.preprocessing.StandardScaler
method), 1837
__init__() (sklearn.qda.QDA method), 1918
__init__() (sklearn.random_projection.GaussianRandomProjection
method), 1846
__init__() (sklearn.random_projection.SparseRandomProjection
method), 1848
__init__() (sklearn.semi_supervised.LabelPropagation
method), 1852
__init__() (sklearn.semi_supervised.LabelSpreading
method), 1855
__init__() (sklearn.svm.LinearSVC method), 1865
__init__() (sklearn.svm.LinearSVR method), 1878
__init__() (sklearn.svm.NuSVC method), 1870
__init__() (sklearn.svm.NuSVR method), 1881
__init__() (sklearn.svm.OneClassSVM method), 1884
__init__() (sklearn.svm.SVC method), 1859
__init__() (sklearn.svm.SVR method), 1874
__init__() (sklearn.tree.DecisionTreeClassifier method),
1893
__init__() (sklearn.tree.DecisionTreeRegressor method),
1899
__init__() (sklearn.tree.ExtraTreeClassifier method),
1903
__init__() (sklearn.tree.ExtraTreeRegressor method),
1907
A
accuracy_score() (in module sklearn.metrics), 1624
AdaBoostClassifier (class in sklearn.ensemble), 1355
AdaBoostRegressor (class in sklearn.ensemble), 1359
add_dummy_feature() (in module sklearn.preprocessing),
1839
additive_chi2_kernel() (in module
sklearn.metrics.pairwise), 1672
AdditiveChi2Sampler (class in
sklearn.kernel_approximation), 1482
2018 Indexscikit-learn user guide, Release 0.18.2
adjusted_mutual_info_score() (in module
sklearn.metrics), 1658
adjusted_rand_score() (in module sklearn.metrics), 1659
affinity_propagation() (in module sklearn.cluster), 1164
AffinityPropagation (class in sklearn.cluster), 1133
AgglomerativeClustering (class in sklearn.cluster), 1135
aic() (sklearn.mixture.DPGMM method), 1954
aic() (sklearn.mixture.GaussianMixture method), 1689
aic() (sklearn.mixture.GMM method), 1952
aic() (sklearn.mixture.VBGMM method), 1958
apply() (sklearn.ensemble.ExtraTreesClassifier method),
430
apply() (sklearn.ensemble.ExtraTreesRegressor method),
436
apply() (sklearn.ensemble.GradientBoostingClassifier
method), 442
apply() (sklearn.ensemble.GradientBoostingRegressor
method), 449
apply() (sklearn.ensemble.RandomForestClassifier
method), 418
apply() (sklearn.ensemble.RandomForestRegressor
method), 424
apply() (sklearn.ensemble.RandomTreesEmbedding
method), 1375
apply() (sklearn.tree.DecisionTreeClassifier method),
1893
apply() (sklearn.tree.DecisionTreeRegressor method),
1899
apply() (sklearn.tree.ExtraTreeClassifier method), 1903
apply() (sklearn.tree.ExtraTreeRegressor method), 1907
ARDRegression (class in sklearn.linear_model), 1502
auc() (in module sklearn.metrics), 1626
average_precision_score() (in module sklearn.metrics),
1626
B
BaggingClassifier (class in sklearn.ensemble), 1363
BaggingRegressor (class in sklearn.ensemble), 1367
BallTree (class in sklearn.neighbors), 1747
BaseEstimator (class in sklearn.base), 1129
BayesianGaussianMixture (class in sklearn.mixture),
1691
BayesianRidge (class in sklearn.linear_model), 1505
BernoulliNB (class in sklearn.naive_bayes), 1716
BernoulliRBM (class in sklearn.neural_network), 1770
bic() (sklearn.mixture.DPGMM method), 1954
bic() (sklearn.mixture.GaussianMixture method), 1689
bic() (sklearn.mixture.GMM method), 1952
bic() (sklearn.mixture.VBGMM method), 1958
biclusters_ (sklearn.cluster.bicluster.SpectralBiclustering
attribute), 1171
biclusters_ (sklearn.cluster.bicluster.SpectralCoclustering
attribute), 1173
binarize() (in module sklearn.preprocessing), 1840
Binarizer (class in sklearn.preprocessing), 1809
Birch (class in sklearn.cluster), 1138
bounds (sklearn.gaussian_process.kernels.CompoundKernel
attribute), 1474
bounds (sklearn.gaussian_process.kernels.ConstantKernel
attribute), 1460
bounds (sklearn.gaussian_process.kernels.DotProduct attribute), 1471
bounds (sklearn.gaussian_process.kernels.Exponentiation
attribute), 1458
bounds (sklearn.gaussian_process.kernels.ExpSineSquared
attribute), 1469
bounds (sklearn.gaussian_process.kernels.Hyperparameter
attribute), 1476
bounds (sklearn.gaussian_process.kernels.Kernel attribute), 1454
bounds (sklearn.gaussian_process.kernels.Matern attribute), 1465
bounds (sklearn.gaussian_process.kernels.PairwiseKernel
attribute), 1473
bounds (sklearn.gaussian_process.kernels.Product attribute), 1457
bounds (sklearn.gaussian_process.kernels.RationalQuadratic
attribute), 1467
bounds (sklearn.gaussian_process.kernels.RBF attribute),
1463
bounds (sklearn.gaussian_process.kernels.Sum attribute),
1455
bounds (sklearn.gaussian_process.kernels.WhiteKernel
attribute), 1462
brier_score_loss() (in module sklearn.metrics), 1628
build_analyzer() (sklearn.feature_extraction.text.CountVectorizer
method), 1399
build_analyzer() (sklearn.feature_extraction.text.HashingVectorizer
method), 1404
build_analyzer() (sklearn.feature_extraction.text.TfidfVectorizer
method), 1411
build_preprocessor() (sklearn.feature_extraction.text.CountVectorizer
method), 1399
build_preprocessor() (sklearn.feature_extraction.text.HashingVectorizer
method), 1404
build_preprocessor() (sklearn.feature_extraction.text.TfidfVectorizer
method), 1411
build_tokenizer() (sklearn.feature_extraction.text.CountVectorizer
method), 1400
build_tokenizer() (sklearn.feature_extraction.text.HashingVectorizer
method), 1404
build_tokenizer() (sklearn.feature_extraction.text.TfidfVectorizer
method), 1411
C
CalibratedClassifierCV (class in sklearn.calibration),
1783
calibration_curve() (in module sklearn.calibration), 1786
Index 2019scikit-learn user guide, Release 0.18.2
calinski_harabaz_score() (in module sklearn.metrics),
1661
CCA (class in sklearn.cross_decomposition), 1796
ChangedBehaviorWarning (class in sklearn.exceptions),
1384
check_cv() (in module sklearn.cross_validation), 1967
check_cv() (in module sklearn.model_selection), 1226
check_estimator() (in module
sklearn.utils.estimator_checks), 1913
check_increasing() (in module sklearn.isotonic), 1481
check_random_state() (in module sklearn.utils), 1912
chi2() (in module sklearn.feature_selection), 1440
chi2_kernel() (in module sklearn.metrics.pairwise), 1673
classification_report() (in module sklearn.metrics), 1629
ClassifierMixin (class in sklearn.base), 1130
clear_data_home() (in module sklearn.datasets), 1250
clone() (in module sklearn.base), 1132
clone_with_theta() (sklearn.gaussian_process.kernels.CompoundKernel
method), 1474
clone_with_theta() (sklearn.gaussian_process.kernels.ConstantKernel
method), 1460
clone_with_theta() (sklearn.gaussian_process.kernels.DotProduct
method), 1471
clone_with_theta() (sklearn.gaussian_process.kernels.Exponentiation
method), 1458
clone_with_theta() (sklearn.gaussian_process.kernels.ExpSineSquared
method), 1469
clone_with_theta() (sklearn.gaussian_process.kernels.Kernel
method), 1454
clone_with_theta() (sklearn.gaussian_process.kernels.Matern
method), 1466
clone_with_theta() (sklearn.gaussian_process.kernels.PairwiseKernel
method), 1473
clone_with_theta() (sklearn.gaussian_process.kernels.Product
method), 1457
clone_with_theta() (sklearn.gaussian_process.kernels.RationalQuadratic
method), 1467
clone_with_theta() (sklearn.gaussian_process.kernels.RBF
method), 1463
clone_with_theta() (sklearn.gaussian_process.kernels.Sum
method), 1455
clone_with_theta() (sklearn.gaussian_process.kernels.WhiteKernel
method), 1462
ClusterMixin (class in sklearn.base), 1131
cohen_kappa_score() (in module sklearn.metrics), 1630
completeness_score() (in module sklearn.metrics), 1661
CompoundKernel (class in
sklearn.gaussian_process.kernels), 1474
confusion_matrix() (in module sklearn.metrics), 1631
consensus_score() (in module sklearn.metrics), 1671
ConstantKernel (class in
sklearn.gaussian_process.kernels), 1459
ConvergenceWarning (class in sklearn.exceptions), 1384
correct_covariance() (sklearn.covariance.EllipticEnvelope
method), 1179
correct_covariance() (sklearn.covariance.MinCovDet
method), 1192
cosine_distances() (in module sklearn.metrics.pairwise),
1680
cosine_similarity() (in module sklearn.metrics.pairwise),
1680
count() (sklearn.gaussian_process.kernels.Hyperparameter
method), 1476
CountVectorizer (class in sklearn.feature_extraction.text),
1397
coverage_error() (in module sklearn.metrics), 1656
cross_val_predict() (in module sklearn.cross_validation),
1965
cross_val_predict() (in module sklearn.model_selection),
1243
cross_val_score() (in module sklearn.cross_validation),
1966
cross_val_score() (in module sklearn.model_selection),
1241
cross_validation() (in module sklearn.svm.libsvm), 1889
D
data_min (sklearn.preprocessing.MinMaxScaler attribute), 1826
data_range (sklearn.preprocessing.MinMaxScaler attribute), 1826
DataConversionWarning (class in sklearn.exceptions),
1384
DataDimensionalityWarning (class in
sklearn.exceptions), 1384
DBSCAN (class in sklearn.cluster), 1141
dbscan() (in module sklearn.cluster), 1165
decision_function() (in module sklearn.svm.libsvm),
1888
decision_function() (sklearn.covariance.EllipticEnvelope
method), 1179
decision_function() (sklearn.discriminant_analysis.LinearDiscriminantAnal
method), 1495
decision_function() (sklearn.discriminant_analysis.QuadraticDiscriminantA
method), 1499
decision_function() (sklearn.ensemble.AdaBoostClassifier
method), 1356
decision_function() (sklearn.ensemble.BaggingClassifier
method), 1365
decision_function() (sklearn.ensemble.GradientBoostingClassifier
method), 442
decision_function() (sklearn.ensemble.GradientBoostingRegressor
method), 450
decision_function() (sklearn.ensemble.IsolationForest
method), 1372
decision_function() (sklearn.grid_search.GridSearchCV
method), 1926
2020 Indexscikit-learn user guide, Release 0.18.2
decision_function() (sklearn.grid_search.RandomizedSearchCV
method), 1931
decision_function() (sklearn.lda.LDA method), 1916
decision_function() (sklearn.linear_model.ARDRegression
method), 1504
decision_function() (sklearn.linear_model.BayesianRidge
method), 1507
decision_function() (sklearn.linear_model.ElasticNet
method), 1511
decision_function() (sklearn.linear_model.ElasticNetCV
method), 367
decision_function() (sklearn.linear_model.HuberRegressor
method), 1515
decision_function() (sklearn.linear_model.Lars method),
1519
decision_function() (sklearn.linear_model.LarsCV
method), 372
decision_function() (sklearn.linear_model.Lasso
method), 1522
decision_function() (sklearn.linear_model.LassoCV
method), 376
decision_function() (sklearn.linear_model.LassoLars
method), 1528
decision_function() (sklearn.linear_model.LassoLarsCV
method), 382
decision_function() (sklearn.linear_model.LassoLarsIC
method), 413
decision_function() (sklearn.linear_model.LinearRegression
method), 1530
decision_function() (sklearn.linear_model.LogisticRegression
method), 1535
decision_function() (sklearn.linear_model.LogisticRegressionCV
method), 386
decision_function() (sklearn.linear_model.MultiTaskElasticNet
method), 1546
decision_function() (sklearn.linear_model.MultiTaskElasticNetCV
method), 392
decision_function() (sklearn.linear_model.MultiTaskLasso
method), 1540
decision_function() (sklearn.linear_model.MultiTaskLassoCV
method), 398
decision_function() (sklearn.linear_model.OrthogonalMatchingPursuit
method), 1550
decision_function() (sklearn.linear_model.OrthogonalMatchingPursuitCV
method), 403
decision_function() (sklearn.linear_model.PassiveAggressiveClassifier
method), 1553
decision_function() (sklearn.linear_model.PassiveAggressiveRegressor
method), 1557
decision_function() (sklearn.linear_model.Perceptron
method), 1560
decision_function() (sklearn.linear_model.Ridge
method), 1576
decision_function() (sklearn.linear_model.RidgeClassifier
method), 1579
decision_function() (sklearn.linear_model.RidgeClassifierCV
method), 409
decision_function() (sklearn.linear_model.RidgeCV
method), 406
decision_function() (sklearn.linear_model.SGDClassifier
method), 1584
decision_function() (sklearn.linear_model.SGDRegressor
method), 1590
decision_function() (sklearn.linear_model.TheilSenRegressor
method), 1594
decision_function() (sklearn.model_selection.GridSearchCV
method), 1231
decision_function() (sklearn.model_selection.RandomizedSearchCV
method), 1236
decision_function() (sklearn.multiclass.OneVsOneClassifier
method), 1701
decision_function() (sklearn.multiclass.OneVsRestClassifier
method), 1699
decision_function() (sklearn.pipeline.Pipeline method),
1802
decision_function() (sklearn.qda.QDA method), 1918
decision_function() (sklearn.svm.LinearSVC method),
1865
decision_function() (sklearn.svm.LinearSVR method),
1878
decision_function() (sklearn.svm.NuSVC method), 1870
decision_function() (sklearn.svm.NuSVR method), 1881
decision_function() (sklearn.svm.OneClassSVM
method), 1884
decision_function() (sklearn.svm.SVC method), 1859
decision_function() (sklearn.svm.SVR method), 1874
decision_path() (sklearn.ensemble.ExtraTreesClassifier
method), 430
decision_path() (sklearn.ensemble.ExtraTreesRegressor
method), 436
decision_path() (sklearn.ensemble.RandomForestClassifier
method), 418
decision_path() (sklearn.ensemble.RandomForestRegressor
method), 424
decision_path() (sklearn.ensemble.RandomTreesEmbedding
method), 1375
decision_path() (sklearn.tree.DecisionTreeClassifier
method), 1893
decision_path() (sklearn.tree.DecisionTreeRegressor
method), 1899
decision_path() (sklearn.tree.ExtraTreeClassifier
method), 1903
decision_path() (sklearn.tree.ExtraTreeRegressor
method), 1908
DecisionTreeClassifier (class in sklearn.tree), 1890
DecisionTreeRegressor (class in sklearn.tree), 1897
Index 2021scikit-learn user guide, Release 0.18.2
decode() (sklearn.feature_extraction.text.CountVectorizer
method), 1400
decode() (sklearn.feature_extraction.text.HashingVectorizer
method), 1404
decode() (sklearn.feature_extraction.text.TfidfVectorizer
method), 1411
densify() (sklearn.linear_model.LogisticRegression
method), 1535
densify() (sklearn.linear_model.LogisticRegressionCV
method), 387
densify() (sklearn.linear_model.PassiveAggressiveClassifier
method), 1554
densify() (sklearn.linear_model.PassiveAggressiveRegressor
method), 1557
densify() (sklearn.linear_model.Perceptron method),
1561
densify() (sklearn.linear_model.SGDClassifier method),
1584
densify() (sklearn.linear_model.SGDRegressor method),
1590
densify() (sklearn.svm.LinearSVC method), 1865
diag() (sklearn.gaussian_process.kernels.CompoundKernel
method), 1474
diag() (sklearn.gaussian_process.kernels.ConstantKernel
method), 1460
diag() (sklearn.gaussian_process.kernels.DotProduct
method), 1471
diag() (sklearn.gaussian_process.kernels.Exponentiation
method), 1458
diag() (sklearn.gaussian_process.kernels.ExpSineSquared
method), 1469
diag() (sklearn.gaussian_process.kernels.Kernel method),
1454
diag() (sklearn.gaussian_process.kernels.Matern
method), 1466
diag() (sklearn.gaussian_process.kernels.PairwiseKernel
method), 1473
diag() (sklearn.gaussian_process.kernels.Product
method), 1457
diag() (sklearn.gaussian_process.kernels.RationalQuadratic
method), 1468
diag() (sklearn.gaussian_process.kernels.RBF method),
1464
diag() (sklearn.gaussian_process.kernels.Sum method),
1455
diag() (sklearn.gaussian_process.kernels.WhiteKernel
method), 1462
dict_learning() (in module sklearn.decomposition), 1345
dict_learning_online() (in module
sklearn.decomposition), 1346
DictionaryLearning (class in sklearn.decomposition),
1332
DictVectorizer (class in sklearn.feature_extraction), 1386
dist_to_rdist() (sklearn.neighbors.DistanceMetric
method), 1764
distance_metrics() (in module sklearn.metrics.pairwise),
1674
DistanceMetric (class in sklearn.neighbors), 1762
DotProduct (class in sklearn.gaussian_process.kernels),
1470
DPGMM (class in sklearn.mixture), 1954
DummyClassifier (class in sklearn.dummy), 1349
DummyRegressor (class in sklearn.dummy), 1352
dump_svmlight_file() (in module sklearn.datasets), 1274
E
EfficiencyWarning (class in sklearn.exceptions), 1385
ElasticNet (class in sklearn.linear_model), 1508
ElasticNetCV (class in sklearn.linear_model), 365
EllipticEnvelope (class in sklearn.covariance), 1177
empirical_covariance() (in module sklearn.covariance),
1200
EmpiricalCovariance (class in sklearn.covariance), 1175
error_norm() (sklearn.covariance.EllipticEnvelope
method), 1179
error_norm() (sklearn.covariance.EmpiricalCovariance
method), 1176
error_norm() (sklearn.covariance.GraphLasso method),
1182
error_norm() (sklearn.covariance.GraphLassoCV
method), 1186
error_norm() (sklearn.covariance.LedoitWolf method),
1188
error_norm() (sklearn.covariance.MinCovDet method),
1192
error_norm() (sklearn.covariance.OAS method), 1195
error_norm() (sklearn.covariance.ShrunkCovariance
method), 1198
estimate_bandwidth() (in module sklearn.cluster), 1160
estimators_samples_ (sklearn.ensemble.BaggingClassifier
attribute), 1365
estimators_samples_ (sklearn.ensemble.BaggingRegressor
attribute), 1369
estimators_samples_ (sklearn.ensemble.IsolationForest
attribute), 1372
euclidean_distances() (in module
sklearn.metrics.pairwise), 1674
explained_variance_score() (in module sklearn.metrics),
1651
Exponentiation (class in
sklearn.gaussian_process.kernels), 1458
export_graphviz() (in module sklearn.tree), 1910
ExpSineSquared (class in
sklearn.gaussian_process.kernels), 1469
extract_patches_2d() (in module
sklearn.feature_extraction.image), 1393
ExtraTreeClassifier (class in sklearn.tree), 1902
2022 Indexscikit-learn user guide, Release 0.18.2
ExtraTreeRegressor (class in sklearn.tree), 1907
ExtraTreesClassifier (class in sklearn.ensemble), 427
ExtraTreesRegressor (class in sklearn.ensemble), 433
F
f1_score() (in module sklearn.metrics), 1632
f_classif() (in module sklearn.feature_selection), 1441
f_regression() (in module sklearn.feature_selection),
1441
FactorAnalysis (class in sklearn.decomposition), 1312
FastICA (class in sklearn.decomposition), 1315
fastica() (in module sklearn.decomposition), 1343
fbeta_score() (in module sklearn.metrics), 1633
feature_importances_ (sklearn.ensemble.AdaBoostClassifier
attribute), 1356
feature_importances_ (sklearn.ensemble.AdaBoostRegressor
attribute), 1361
feature_importances_ (sklearn.ensemble.ExtraTreesClassifier
attribute), 430
feature_importances_ (sklearn.ensemble.ExtraTreesRegressor
attribute), 436
feature_importances_ (sklearn.ensemble.GradientBoostingClassifier
attribute), 443
feature_importances_ (sklearn.ensemble.GradientBoostingRegressor
attribute), 450
feature_importances_ (sklearn.ensemble.RandomForestClassifier
attribute), 418
feature_importances_ (sklearn.ensemble.RandomForestRegressor
attribute), 425
feature_importances_ (sklearn.ensemble.RandomTreesEmbedding
attribute), 1376
feature_importances_ (sklearn.tree.DecisionTreeClassifier
attribute), 1893
feature_importances_ (sklearn.tree.DecisionTreeRegressor
attribute), 1900
feature_importances_ (sklearn.tree.ExtraTreeClassifier
attribute), 1904
feature_importances_ (sklearn.tree.ExtraTreeRegressor
attribute), 1908
FeatureAgglomeration (class in sklearn.cluster), 1143
FeatureHasher (class in sklearn.feature_extraction), 1389
FeatureUnion (class in sklearn.pipeline), 1805
fetch_20newsgroups() (in module sklearn.datasets), 1250
fetch_20newsgroups_vectorized() (in module
sklearn.datasets), 1251
fetch_california_housing() (in module sklearn.datasets),
1264
fetch_covtype() (in module sklearn.datasets), 1265
fetch_kddcup99() (in module sklearn.datasets), 1266
fetch_lfw_pairs() (in module sklearn.datasets), 1259
fetch_lfw_people() (in module sklearn.datasets), 1260
fetch_mldata() (in module sklearn.datasets), 1262
fetch_olivetti_faces() (in module sklearn.datasets), 1263
fetch_rcv1() (in module sklearn.datasets), 1267
fetch_species_distributions() (in module
sklearn.datasets), 1270
fit() (in module sklearn.svm.libsvm), 1886
fit() (sklearn.calibration.CalibratedClassifierCV method),
1784
fit() (sklearn.cluster.AffinityPropagation method), 1134
fit() (sklearn.cluster.AgglomerativeClustering method),
1137
fit() (sklearn.cluster.bicluster.SpectralBiclustering
method), 1171
fit() (sklearn.cluster.bicluster.SpectralCoclustering
method), 1174
fit() (sklearn.cluster.Birch method), 1139
fit() (sklearn.cluster.DBSCAN method), 1142
fit() (sklearn.cluster.FeatureAgglomeration method),
1145
fit() (sklearn.cluster.KMeans method), 1150
fit() (sklearn.cluster.MeanShift method), 1156
fit() (sklearn.cluster.MiniBatchKMeans method), 1153
fit() (sklearn.cluster.SpectralClustering method), 1159
fit() (sklearn.covariance.EmpiricalCovariance method),
1176
fit() (sklearn.covariance.GraphLassoCV method), 1186
fit() (sklearn.covariance.LedoitWolf method), 1189
fit() (sklearn.covariance.MinCovDet method), 1192
fit() (sklearn.covariance.OAS method), 1196
fit() (sklearn.covariance.ShrunkCovariance method),
1198
fit() (sklearn.cross_decomposition.CCA method), 1797
fit() (sklearn.cross_decomposition.PLSCanonical
method), 1794
fit() (sklearn.cross_decomposition.PLSRegression
method), 1789
fit() (sklearn.decomposition.DictionaryLearning method),
1334
fit() (sklearn.decomposition.FactorAnalysis method),
1314
fit() (sklearn.decomposition.FastICA method), 1317
fit() (sklearn.decomposition.IncrementalPCA method),
1303
fit() (sklearn.decomposition.KernelPCA method), 1311
fit() (sklearn.decomposition.LatentDirichletAllocation
method), 1341
fit() (sklearn.decomposition.MiniBatchDictionaryLearning
method), 1337
fit() (sklearn.decomposition.MiniBatchSparsePCA
method), 1329
fit() (sklearn.decomposition.NMF method), 1324
fit() (sklearn.decomposition.PCA method), 1298
fit() (sklearn.decomposition.ProjectedGradientNMF
method), 1308
fit() (sklearn.decomposition.RandomizedPCA method),
1945
fit() (sklearn.decomposition.SparseCoder method), 1331
Index 2023scikit-learn user guide, Release 0.18.2
fit() (sklearn.decomposition.SparsePCA method), 1326
fit() (sklearn.decomposition.TruncatedSVD method),
1319
fit() (sklearn.discriminant_analysis.LinearDiscriminantAnalysis
method), 1495
fit() (sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis
method), 1499
fit() (sklearn.dummy.DummyClassifier method), 1350
fit() (sklearn.dummy.DummyRegressor method), 1353
fit() (sklearn.ensemble.AdaBoostClassifier method), 1356
fit() (sklearn.ensemble.AdaBoostRegressor method),
1361
fit() (sklearn.ensemble.BaggingClassifier method), 1365
fit() (sklearn.ensemble.BaggingRegressor method), 1369
fit() (sklearn.ensemble.ExtraTreesClassifier method), 431
fit() (sklearn.ensemble.ExtraTreesRegressor method),
437
fit() (sklearn.ensemble.GradientBoostingClassifier
method), 443
fit() (sklearn.ensemble.GradientBoostingRegressor
method), 450
fit() (sklearn.ensemble.IsolationForest method), 1372
fit() (sklearn.ensemble.RandomForestClassifier method),
418
fit() (sklearn.ensemble.RandomForestRegressor method),
425
fit() (sklearn.ensemble.RandomTreesEmbedding
method), 1376
fit() (sklearn.ensemble.VotingClassifier method), 1378
fit() (sklearn.feature_extraction.DictVectorizer method),
1387
fit() (sklearn.feature_extraction.FeatureHasher method),
1391
fit() (sklearn.feature_extraction.image.PatchExtractor
method), 1395
fit() (sklearn.feature_extraction.text.CountVectorizer
method), 1400
fit() (sklearn.feature_extraction.text.HashingVectorizer
method), 1404
fit() (sklearn.feature_extraction.text.TfidfTransformer
method), 1406
fit() (sklearn.feature_extraction.text.TfidfVectorizer
method), 1411
fit() (sklearn.feature_selection.GenericUnivariateSelect
method), 1414
fit() (sklearn.feature_selection.RFE method), 1432
fit() (sklearn.feature_selection.RFECV method), 1436
fit() (sklearn.feature_selection.SelectFdr method), 1424
fit() (sklearn.feature_selection.SelectFpr method), 1422
fit() (sklearn.feature_selection.SelectFromModel
method), 1426
fit() (sklearn.feature_selection.SelectFwe method), 1429
fit() (sklearn.feature_selection.SelectKBest method),
1419
fit() (sklearn.feature_selection.SelectPercentile method),
1416
fit() (sklearn.feature_selection.VarianceThreshold
method), 1438
fit() (sklearn.gaussian_process.GaussianProcess method),
1949
fit() (sklearn.gaussian_process.GaussianProcessClassifier
method), 1451
fit() (sklearn.gaussian_process.GaussianProcessRegressor
method), 1447
fit() (sklearn.grid_search.GridSearchCV method), 1926
fit() (sklearn.grid_search.RandomizedSearchCV
method), 1931
fit() (sklearn.isotonic.IsotonicRegression method), 1478
fit() (sklearn.kernel_approximation.AdditiveChi2Sampler
method), 1482
fit() (sklearn.kernel_approximation.Nystroem method),
1485
fit() (sklearn.kernel_approximation.RBFSampler
method), 1486
fit() (sklearn.kernel_approximation.SkewedChi2Sampler
method), 1488
fit() (sklearn.kernel_ridge.KernelRidge method), 1491
fit() (sklearn.lda.LDA method), 1916
fit() (sklearn.linear_model.ARDRegression method),
1504
fit() (sklearn.linear_model.BayesianRidge method), 1507
fit() (sklearn.linear_model.ElasticNet method), 1511
fit() (sklearn.linear_model.ElasticNetCV method), 367
fit() (sklearn.linear_model.HuberRegressor method),
1516
fit() (sklearn.linear_model.Lars method), 1519
fit() (sklearn.linear_model.LarsCV method), 372
fit() (sklearn.linear_model.Lasso method), 1522
fit() (sklearn.linear_model.LassoCV method), 376
fit() (sklearn.linear_model.LassoLars method), 1528
fit() (sklearn.linear_model.LassoLarsCV method), 382
fit() (sklearn.linear_model.LassoLarsIC method), 413
fit() (sklearn.linear_model.LinearRegression method),
1530
fit() (sklearn.linear_model.LogisticRegression method),
1535
fit() (sklearn.linear_model.LogisticRegressionCV
method), 387
fit() (sklearn.linear_model.MultiTaskElasticNet method),
1546
fit() (sklearn.linear_model.MultiTaskElasticNetCV
method), 393
fit() (sklearn.linear_model.MultiTaskLasso method),
1541
fit() (sklearn.linear_model.MultiTaskLassoCV method),
398
fit() (sklearn.linear_model.OrthogonalMatchingPursuit
method), 1551
2024 Indexscikit-learn user guide, Release 0.18.2
fit() (sklearn.linear_model.OrthogonalMatchingPursuitCV
method), 403
fit() (sklearn.linear_model.PassiveAggressiveClassifier
method), 1554
fit() (sklearn.linear_model.PassiveAggressiveRegressor
method), 1557
fit() (sklearn.linear_model.Perceptron method), 1561
fit() (sklearn.linear_model.RandomizedLasso method),
1566
fit() (sklearn.linear_model.RandomizedLogisticRegression
method), 1569
fit() (sklearn.linear_model.RANSACRegressor method),
1572
fit() (sklearn.linear_model.Ridge method), 1576
fit() (sklearn.linear_model.RidgeClassifier method), 1579
fit() (sklearn.linear_model.RidgeClassifierCV method),
409
fit() (sklearn.linear_model.RidgeCV method), 406
fit() (sklearn.linear_model.SGDClassifier method), 1584
fit() (sklearn.linear_model.SGDRegressor method), 1590
fit() (sklearn.linear_model.TheilSenRegressor method),
1595
fit() (sklearn.manifold.Isomap method), 1610
fit() (sklearn.manifold.LocallyLinearEmbedding
method), 1608
fit() (sklearn.manifold.MDS method), 1613
fit() (sklearn.manifold.SpectralEmbedding method), 1615
fit() (sklearn.manifold.TSNE method), 1619
fit() (sklearn.mixture.BayesianGaussianMixture method),
1695
fit() (sklearn.mixture.DPGMM method), 1955
fit() (sklearn.mixture.GaussianMixture method), 1689
fit() (sklearn.mixture.GMM method), 1952
fit() (sklearn.mixture.VBGMM method), 1958
fit() (sklearn.model_selection.GridSearchCV method),
1231
fit() (sklearn.model_selection.RandomizedSearchCV
method), 1237
fit() (sklearn.multiclass.OneVsOneClassifier method),
1702
fit() (sklearn.multiclass.OneVsRestClassifier method),
1699
fit() (sklearn.multiclass.OutputCodeClassifier method),
1704
fit() (sklearn.multioutput.MultiOutputClassifier method),
1708
fit() (sklearn.multioutput.MultiOutputRegressor method),
1706
fit() (sklearn.naive_bayes.BernoulliNB method), 1717
fit() (sklearn.naive_bayes.GaussianNB method), 1710
fit() (sklearn.naive_bayes.MultinomialNB method), 1714
fit() (sklearn.neighbors.KernelDensity method), 1766
fit() (sklearn.neighbors.KNeighborsClassifier method),
1728
fit() (sklearn.neighbors.KNeighborsRegressor method),
1737
fit() (sklearn.neighbors.LSHForest method), 1759
fit() (sklearn.neighbors.NearestCentroid method), 1745
fit() (sklearn.neighbors.NearestNeighbors method), 1722
fit() (sklearn.neighbors.RadiusNeighborsClassifier
method), 1732
fit() (sklearn.neighbors.RadiusNeighborsRegressor
method), 1741
fit() (sklearn.neural_network.BernoulliRBM method),
1771
fit() (sklearn.neural_network.MLPClassifier method),
1776
fit() (sklearn.neural_network.MLPRegressor method),
1782
fit() (sklearn.pipeline.FeatureUnion method), 1806
fit() (sklearn.pipeline.Pipeline method), 1802
fit() (sklearn.preprocessing.Binarizer method), 1809
fit() (sklearn.preprocessing.Imputer method), 1813
fit() (sklearn.preprocessing.KernelCenterer method),
1814
fit() (sklearn.preprocessing.LabelBinarizer method), 1817
fit() (sklearn.preprocessing.LabelEncoder method), 1820
fit() (sklearn.preprocessing.MaxAbsScaler method), 1823
fit() (sklearn.preprocessing.MinMaxScaler method), 1826
fit() (sklearn.preprocessing.MultiLabelBinarizer method),
1821
fit() (sklearn.preprocessing.Normalizer method), 1828
fit() (sklearn.preprocessing.OneHotEncoder method),
1830
fit() (sklearn.preprocessing.PolynomialFeatures method),
1833
fit() (sklearn.preprocessing.RobustScaler method), 1835
fit() (sklearn.preprocessing.StandardScaler method),
1837
fit() (sklearn.qda.QDA method), 1919
fit() (sklearn.random_projection.GaussianRandomProjection
method), 1846
fit() (sklearn.random_projection.SparseRandomProjection
method), 1848
fit() (sklearn.semi_supervised.LabelPropagation method),
1852
fit() (sklearn.semi_supervised.LabelSpreading method),
1855
fit() (sklearn.svm.LinearSVC method), 1865
fit() (sklearn.svm.LinearSVR method), 1878
fit() (sklearn.svm.NuSVC method), 1870
fit() (sklearn.svm.NuSVR method), 1881
fit() (sklearn.svm.OneClassSVM method), 1884
fit() (sklearn.svm.SVC method), 1859
fit() (sklearn.svm.SVR method), 1875
fit() (sklearn.tree.DecisionTreeClassifier method), 1894
fit() (sklearn.tree.DecisionTreeRegressor method), 1900
fit() (sklearn.tree.ExtraTreeClassifier method), 1904
Index 2025scikit-learn user guide, Release 0.18.2
fit() (sklearn.tree.ExtraTreeRegressor method), 1908
fit_grid_point() (in module sklearn.grid_search), 1960
fit_grid_point() (in module sklearn.model_selection),
1240
fit_predict() (sklearn.base.ClusterMixin method), 1131
fit_predict() (sklearn.cluster.AffinityPropagation
method), 1134
fit_predict() (sklearn.cluster.AgglomerativeClustering
method), 1137
fit_predict() (sklearn.cluster.Birch method), 1139
fit_predict() (sklearn.cluster.DBSCAN method), 1142
fit_predict() (sklearn.cluster.KMeans method), 1150
fit_predict() (sklearn.cluster.MeanShift method), 1156
fit_predict() (sklearn.cluster.MiniBatchKMeans method),
1153
fit_predict() (sklearn.cluster.SpectralClustering method),
1160
fit_predict() (sklearn.mixture.DPGMM method), 1955
fit_predict() (sklearn.mixture.GMM method), 1952
fit_predict() (sklearn.mixture.VBGMM method), 1959
fit_predict() (sklearn.pipeline.Pipeline method), 1803
fit_transform() (sklearn.base.TransformerMixin method),
1132
fit_transform() (sklearn.cluster.Birch method), 1139
fit_transform() (sklearn.cluster.FeatureAgglomeration
method), 1145
fit_transform() (sklearn.cluster.KMeans method), 1150
fit_transform() (sklearn.cluster.MiniBatchKMeans
method), 1153
fit_transform() (sklearn.cross_decomposition.CCA
method), 1798
fit_transform() (sklearn.cross_decomposition.PLSCanonical
method), 1794
fit_transform() (sklearn.cross_decomposition.PLSRegression
method), 1789
fit_transform() (sklearn.cross_decomposition.PLSSVD
method), 1800
fit_transform() (sklearn.decomposition.DictionaryLearning
method), 1334
fit_transform() (sklearn.decomposition.FactorAnalysis
method), 1314
fit_transform() (sklearn.decomposition.FastICA method),
1317
fit_transform() (sklearn.decomposition.IncrementalPCA
method), 1303
fit_transform() (sklearn.decomposition.KernelPCA
method), 1311
fit_transform() (sklearn.decomposition.LatentDirichletAllocation
method), 1341
fit_transform() (sklearn.decomposition.MiniBatchDictionaryLearning
method), 1338
fit_transform() (sklearn.decomposition.MiniBatchSparsePCA
method), 1329
fit_transform() (sklearn.decomposition.NMF method),
1324
fit_transform() (sklearn.decomposition.PCA method),
1298
fit_transform() (sklearn.decomposition.ProjectedGradientNMF
method), 1308
fit_transform() (sklearn.decomposition.RandomizedPCA
method), 1946
fit_transform() (sklearn.decomposition.SparseCoder
method), 1331
fit_transform() (sklearn.decomposition.SparsePCA
method), 1326
fit_transform() (sklearn.decomposition.TruncatedSVD
method), 1320
fit_transform() (sklearn.discriminant_analysis.LinearDiscriminantAnalysis
method), 1495
fit_transform() (sklearn.ensemble.ExtraTreesClassifier
method), 431
fit_transform() (sklearn.ensemble.ExtraTreesRegressor
method), 437
fit_transform() (sklearn.ensemble.GradientBoostingClassifier
method), 443
fit_transform() (sklearn.ensemble.GradientBoostingRegressor
method), 450
fit_transform() (sklearn.ensemble.RandomForestClassifier
method), 419
fit_transform() (sklearn.ensemble.RandomForestRegressor
method), 425
fit_transform() (sklearn.ensemble.RandomTreesEmbedding
method), 1376
fit_transform() (sklearn.ensemble.VotingClassifier
method), 1378
fit_transform() (sklearn.feature_extraction.DictVectorizer
method), 1387
fit_transform() (sklearn.feature_extraction.FeatureHasher
method), 1391
fit_transform() (sklearn.feature_extraction.text.CountVectorizer
method), 1400
fit_transform() (sklearn.feature_extraction.text.HashingVectorizer
method), 1404
fit_transform() (sklearn.feature_extraction.text.TfidfTransformer
method), 1406
fit_transform() (sklearn.feature_extraction.text.TfidfVectorizer
method), 1411
fit_transform() (sklearn.feature_selection.GenericUnivariateSelect
method), 1414
fit_transform() (sklearn.feature_selection.RFE method),
1432
fit_transform() (sklearn.feature_selection.RFECV
method), 1436
fit_transform() (sklearn.feature_selection.SelectFdr
method), 1424
fit_transform() (sklearn.feature_selection.SelectFpr
method), 1422
2026 Indexscikit-learn user guide, Release 0.18.2
fit_transform() (sklearn.feature_selection.SelectFromModel
method), 1426
fit_transform() (sklearn.feature_selection.SelectFwe
method), 1429
fit_transform() (sklearn.feature_selection.SelectKBest
method), 1419
fit_transform() (sklearn.feature_selection.SelectPercentile
method), 1417
fit_transform() (sklearn.feature_selection.VarianceThreshold
method), 1438
fit_transform() (sklearn.isotonic.IsotonicRegression
method), 1478
fit_transform() (sklearn.kernel_approximation.AdditiveChi2Sampler
method), 1482
fit_transform() (sklearn.kernel_approximation.Nystroem
method), 1485
fit_transform() (sklearn.kernel_approximation.RBFSampler
method), 1487
fit_transform() (sklearn.kernel_approximation.SkewedChi2Sampler
method), 1488
fit_transform() (sklearn.lda.LDA method), 1916
fit_transform() (sklearn.linear_model.LogisticRegression
method), 1536
fit_transform() (sklearn.linear_model.LogisticRegressionCV
method), 387
fit_transform() (sklearn.linear_model.Perceptron
method), 1561
fit_transform() (sklearn.linear_model.RandomizedLasso
method), 1566
fit_transform() (sklearn.linear_model.RandomizedLogisticRegression
method), 1569
fit_transform() (sklearn.linear_model.SGDClassifier
method), 1584
fit_transform() (sklearn.linear_model.SGDRegressor
method), 1591
fit_transform() (sklearn.manifold.Isomap method), 1611
fit_transform() (sklearn.manifold.LocallyLinearEmbedding
method), 1608
fit_transform() (sklearn.manifold.MDS method), 1613
fit_transform() (sklearn.manifold.SpectralEmbedding
method), 1615
fit_transform() (sklearn.manifold.TSNE method), 1619
fit_transform() (sklearn.neural_network.BernoulliRBM
method), 1772
fit_transform() (sklearn.pipeline.FeatureUnion method),
1806
fit_transform() (sklearn.pipeline.Pipeline method), 1803
fit_transform() (sklearn.preprocessing.Binarizer method),
1810
fit_transform() (sklearn.preprocessing.FunctionTransformer
method), 1811
fit_transform() (sklearn.preprocessing.Imputer method),
1813
fit_transform() (sklearn.preprocessing.KernelCenterer
method), 1815
fit_transform() (sklearn.preprocessing.LabelBinarizer
method), 1817
fit_transform() (sklearn.preprocessing.LabelEncoder
method), 1820
fit_transform() (sklearn.preprocessing.MaxAbsScaler
method), 1823
fit_transform() (sklearn.preprocessing.MinMaxScaler
method), 1826
fit_transform() (sklearn.preprocessing.MultiLabelBinarizer
method), 1822
fit_transform() (sklearn.preprocessing.Normalizer
method), 1828
fit_transform() (sklearn.preprocessing.OneHotEncoder
method), 1831
fit_transform() (sklearn.preprocessing.PolynomialFeatures
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