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Results 51 - 60 of 579 for cms (0.06 seconds)
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RBF SVM parameters — scikit-learn 1.8.0 d...
cm . RdBu ) plt . scatter ( X_2d...1 ], c = y_2d , cmap = plt . cm . RdBu_r , edgecolors = "k"...scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html -
Sparse inverse covariance estimation — sc...
cm . RdBu_r ) plt . xticks (())..., vmax = vmax , cmap = plt . cm . RdBu_r , ) plt . xticks (())...scikit-learn.org/stable/auto_examples/covariance/plot_sparse_cov.html -
Explicit feature map approximation for RBF kern...
cm . tab10 , vmin = 0 , vmax = 10...targets_train , cmap = plt . cm . tab10 , edgecolors = ( 0 ,...scikit-learn.org/stable/auto_examples/miscellaneous/plot_kernel_approximation.html -
Plot different SVM classifiers in the iris data...
cm . coolwarm , alpha = 0.8 , ax...X0 , X1 , c = y , cmap = plt . cm . coolwarm , s = 20 , edgecolors...scikit-learn.org/stable/auto_examples/svm/plot_iris_svc.html -
Iso-probability lines for Gaussian Processes cl...
as np from matplotlib import cm from matplotlib import pyplot...plt . imshow ( y_prob , cmap = cm . gray_r , alpha = 0.8 , extent...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_isoprobability.html -
2011-01-01から1ヶ月間の記事一覧 - はてなニュース
ドナルド「ハッピーセット『スポンジ・ボブ』」のCM。TwitterではCMを真似して「ｼｬﾍﾞｯﾀｱｱｱｱｱｱｱｱｱｱｱ...ポンジ・ボブ」のCMで、おもちゃで大はしゃぎする子どもたちのテンションの高さが話題になっています。CMを見た人からは、「...hatenanews.com/archive/2011/01 -
ConfusionMatrixDisplay — scikit-learn 1.8...
predict ( X_test ) >>> cm = confusion_matrix ( y_test ,...ConfusionMatrixDispl ( confusion_matrix = cm , ... display_labels = clf ....scikit-learn.org/stable/modules/generated/sklearn.metrics.ConfusionMatrixDisplay.html -
Illustration of Gaussian process classification...
cm . PuOr_r , ) contours = plt ....s = 30 , c = Y , cmap = plt . cm . Paired , edgecolors = ( 0 ,...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_xor.html -
SVM: Weighted samples — scikit-learn 1.8....
cm . bone , edgecolors = "black"...0.75 , ax = axis , cmap = plt . cm . bone , ) axis . axis ( "off"...scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html -
Face completion with a multi-output estimators ...
cm . gray , interpolation = "nearest"...( image_shape ), cmap = plt . cm . gray , interpolation = "nearest"...scikit-learn.org/stable/auto_examples/miscellaneous/plot_multioutput_face_completion.html