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Results 31 - 40 of 110 for cms (0.03 sec)
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Image denoising using dictionary learning — sci...
cm . gray , interpolation = "nearest"...0.5 , vmax = 0.5 , cmap = plt . cm . PuOr , interpolation = "nearest"...scikit-learn.org/stable/auto_examples/decomposition/plot_image_denoising.html -
RBF SVM parameters — scikit-learn 1.4.2 documen...
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 -
Manifold learning on handwritten digits: Locall...
cm . binary ) ax . axis ( "off"...} $" , s = 60 , color = plt . cm . Dark2 ( digit ), alpha = 0.425...scikit-learn.org/stable/auto_examples/manifold/plot_lle_digits.html -
Visualizing the stock market structure — scikit...
cm . nipy_spectral ) # Plot the...segments , zorder = 0 , cmap = plt . cm . hot_r , norm = plt . Normalize...scikit-learn.org/stable/auto_examples/applications/plot_stock_market.html -
Nearest Neighbors Classification — scikit-learn...
[[ "sepal length (cm)" , "sepal width (cm)" ]] y = iris . target...scikit-learn.org/stable/auto_examples/neighbors/plot_classification.html -
SVM: Weighted samples — scikit-learn 1.4.2 docu...
cm . bone ) axis . scatter ( X [:,..., alpha = 0.9 , cmap = plt . cm . bone , edgecolors = "black"...scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.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 with custom kernel — scikit-learn 1.4.2 doc...
cm . Paired , ax = ax , response_method...[:, 1 ], c = Y , cmap = plt . cm . Paired , edgecolors = "k" )...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
Plot the decision surface of decision trees tra...
cm . RdYlBu , response_method =...target_names [ i ], cmap = plt . cm . RdYlBu , edgecolor = "black"...scikit-learn.org/stable/auto_examples/tree/plot_iris_dtc.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