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Plot classification boundaries with different S...
0.4 ], [ - 0.5 , 1.2 ], [ - 1.5 , 2.1 ], [ 1.0 , 1.0 ], [ 1.3...array ([ 0 , 0 , 0 , 0 , 0 , 0 , 0 , 0 , 1 , 1 , 1 , 1 , 1 , 1 ,...scikit-learn.org/stable/auto_examples/svm/plot_svm_kernels.html -
Selecting dimensionality reduction with Pipelin...
', MinMaxScaler()), ('reduce_dim', 'passthrough'), ('classify',...{'classify__C': [1, 10, ...], 'reduce_dim': [SelectKBest(s...7f48a4c1dfc0>)],...scikit-learn.org/stable/auto_examples/compose/plot_compare_reduction.html -
Approximate nearest neighbors in TSNE — scikit-...
= { "euclidean" : "l2" , "cosine" : "cosinesimil" , "l1" : "l1"..."MNIST_10000" , load_mnist ( n_samples = 10_000 )), ( "MNIST_20000" , load_mnist...scikit-learn.org/stable/auto_examples/neighbors/approximate_nearest_neighbors.html -
RBF SVM parameters — scikit-learn 1.7.1 documen...
parameters are {'C': np.float64(1.0), 'gamma': np.float64(0.1)} with a...self . midpoint , self . vmax ], [ 0 , 0.5 , 1 ] return np . ma...scikit-learn.org/stable/auto_examples/svm/plot_rbf_parameters.html -
t-SNE: The effect of various perplexity values ...
scatter ( X [ red , 0 ], X [ red , 1 ], c = "r" ) ax . scatter ( X...[ green , 0 ], X [ green , 1 ], c = "g" ) ax . xaxis . set_major_formatter...scikit-learn.org/stable/auto_examples/manifold/plot_t_sne_perplexity.html -
sklearn.decomposition — scikit-learn 1.7.1 docu...
Factorization (NMF). PCA Principal component analysis (PCA). SparseCoder...algorithms. These include PCA, NMF, ICA, and more. Most of the...scikit-learn.org/stable/api/sklearn.decomposition.html -
SVM: Weighted samples — scikit-learn 1.7.1 docu...
weights = [ 0.9 , 0.1 ], random_state = 0 , ) # down-sample for plotting...plot.""" axis . scatter ( X_plot [:, 0 ], X_plot [:, 1 ], c =...scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html -
SVM: Separating hyperplane for unbalanced class...
n_samples_2 = 100 centers = [[ 0.0 , 0.0 ], [ 2.0 , 2.0 ]] clusters_std...svm . SVC ( kernel = "linear" , C = 1.0 ) clf . fit ( X , y )...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane_unbalanced.html -
4. Metadata Routing — scikit-learn 1.7.1 docume...
.. lr , ... X , ... y , ... params = { "sample_weight" : my_weights...my_weights , "groups" : my_groups }, ... cv = GroupKFold (), ... scoring...scikit-learn.org/stable/metadata_routing.html -
SGDClassifier — scikit-learn 1.7.1 documentation
{‘hinge’, ‘log_loss’, ‘modified_huber’, ‘squared_hinge’, ‘perceptron’,...‘perceptron’, ‘squared_error’, ‘huber’, ‘epsilon_insensitive’, ‘squar...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html