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make_scorer — scikit-learn 1.8.0 document...
beta = 2 ) >>> ftwo_scorer ma...response_method='predict', beta=2) >>> from sklearn.model_selection...scikit-learn.org/stable/modules/generated/sklearn.metrics.make_scorer.html -
Plotting Learning Curves and Checking Models’ S...
subplots ( nrows = 2 , ncols = 2 , figsize = ( 16 , 12 ),...subplots ( nrows = 1 , ncols = 2 , figsize = ( 10 , 6 ), sharey...scikit-learn.org/stable/auto_examples/model_selection/plot_learning_curve.html -
卸载步骤
2 步骤 2: 删除 OpenSearch 删除 OpenSearch...rm -rf /path/to/opensearch-3.3.2 步骤 3: 删除数据目录（可选） 默认情况下，数据目录在 Fess...fess.codelibs.org/zh-cn/15.3/install/uninstall.html -
Multilabel classification — scikit-learn ...
subplot ( 2 , 2 , subplot ) plt . title ( title..."none" , linewidths = 2 , label = "Class 2" , ) plot_hyperplane...scikit-learn.org/stable/auto_examples/miscellaneous/plot_multilabel.html -
FeatureHasher — scikit-learn 1.8.0 docume...
'cat' : 2 , 'elephant' : 4 },{ 'dog' : 2 , 'run'...0., 0., 0., 0., 0., 2.], [ 0., 0., 0., -2., -5., 0., 0., 0., 0.,...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
SpectralCoclustering — scikit-learn 1.8.0...
[ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...SpectralCoclustering ( n_clusters = 2 , random_state = 0 ) . fit ( X...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralCoclustering.html -
Sparse coding with a precomputed dictionary ...
) ** 2 / width ** 2 ) * np . exp ( - (( x - center ) ** 2 ) /.../ ( 2 * width ** 2 )) ) return x def ricker_matrix ( width , resolution...scikit-learn.org/stable/auto_examples/decomposition/plot_sparse_coding.html -
GaussianMixture — scikit-learn 1.8.0 docu...
2 ], [ 1 , 4 ], [ 1 , 0 ], [ 10 , 2 ], [ 10 , 4 ],...gm . means_ array([[10., 2.], [ 1., 2.]]) >>> gm . predict...scikit-learn.org/stable/modules/generated/sklearn.mixture.GaussianMixture.html -
Gaussian Processes regression: basic introducto...
length_scale_bounds = ( 1e-2 , 1e2 )) gaussian_process = GaussianProcessRegre...gaussian_process . kernel_ 5.02**2 * RBF(length_scale=1.43) After...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_noisy_targets.html -
Kernel — scikit-learn 1.8.0 documentation
length_scale = 2.0 ) >>> X = np . array ([[ 1 , 2 ], [ 3 ,..., X if Y is None else Y ) ** 2 ... def diag ( self , X ): ......scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Kernel.html