naive_bayes.MultinomialNB()
  • References/Python/scikit-learn/API Reference/naive_bayes

class sklearn.naive_bayes.MultinomialNB(alpha=1.0, fit_prior=True, class_prior=None)

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Linear Regression Example
  • References/Python/scikit-learn/Examples/Generalized Linear Models

This example uses the only the first feature of the diabetes dataset, in order to illustrate a two-dimensional plot of this regression technique. The

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multiclass.OneVsRestClassifier()
  • References/Python/scikit-learn/API Reference/multiclass

class sklearn.multiclass.OneVsRestClassifier(estimator, n_jobs=1)

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neighbors.KNeighborsRegressor()
  • References/Python/scikit-learn/API Reference/neighbors

class sklearn.neighbors.KNeighborsRegressor(n_neighbors=5, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski'

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sklearn.feature_extraction.image.img_to_graph()
  • References/Python/scikit-learn/API Reference/feature_extraction

sklearn.feature_extraction.image.img_to_graph(img, mask=None, return_as=, dtype=None)

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scikit-learn Tutorials
  • References/Python/scikit-learn/Tutorials

An introduction to machine learning

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sklearn.cross_validation.permutation_test_score()
  • References/Python/scikit-learn/API Reference/cross_validation

Warning DEPRECATED

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sklearn.cross_validation.cross_val_predict()
  • References/Python/scikit-learn/API Reference/cross_validation

Warning DEPRECATED

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base.BaseEstimator
  • References/Python/scikit-learn/API Reference/base

class sklearn.base.BaseEstimator

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feature_selection.SelectFromModel()
  • References/Python/scikit-learn/API Reference/feature_selection

class sklearn.feature_selection.SelectFromModel(estimator, threshold=None, prefit=False)

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