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1.4. Support Vector Machines — scikit-lea...
[ 2 , 2 ]] >>> y = [ 0.5 , 2.5 ] >>>...>>> clf . predict ([[ 2. , 2. ]]) array([1]) SVMs decision...scikit-learn.org/stable/modules/svm.html -
ElasticNet — scikit-learn 1.8.0 documenta...
\[\frac{1}{2 n_{\rm samples}} \cdot \|y - X w\|_2^2 + \alpha \cdot...is: ( 1 / ( 2 * n_samples )) * || Y - XW || _Fro ^ 2 + alpha *...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html -
train_test_split — scikit-learn 1.8.0 doc...
2 1 4.9 3.0 1.4 0.2 2 4.7 3.2 1.3 0.2 3 4.6 3.1 1.5...73 6.1 2.8 4.7 1.2 18 5.7 3.8 1.7 0.3 118 7.7 2.6 6.9 2.3 78 6.0...scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html -
Plot different SVM classifiers in the iris data...
subplots ( 2 , 2 ) plt . subplots_adjust ( wspace...dataset. We only consider the first 2 features of this dataset: Sepal...scikit-learn.org/stable/auto_examples/svm/plot_iris_svc.html -
Exponentiation — scikit-learn 1.8.0 docum...
2) is equivalent to using the **...** operator with RBF() ** 2 . Read more in the User Guide . Added...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Exponentiation.html -
Two-class AdaBoost — scikit-learn 1.8.0 d...
cov = 2.0 , n_samples = 200 , n_features = 2 , n_classes = 2 , random_state...= 300 , n_features = 2 , n_classes = 2 , random_state = 1 ) X...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html -
index.css
--sk-landing-bg-2: var(--sk-cyan-shades-2); --sk-landing-bg-3:...var(--sk-cyan-shades-3); --sk-landing-bg-2: var(--sk-cyan); --sk-landing-bg-3:...scikit-learn.org/stable/_static/styles/index.css -
Principal Component Regression vs Partial Least...
n_samples ) / 2 fig , axes = plt . subplots ( 1 , 2 , figsize =...) pca = PCA ( n_components = 2 ) . fit ( X ) plt . scatter (...scikit-learn.org/stable/auto_examples/cross_decomposition/plot_pcr_vs_pls.html -
IncrementalPCA — scikit-learn 1.8.0 docum...
[ - 2 , - 1 ], [ - 3 , - 2 ], ... [ 1 , 1 ], [ 2 , 1 ], [...O(batch_size * n_features ** 2) , but only 2 * batch_size samples remain...scikit-learn.org/stable/modules/generated/sklearn.decomposition.IncrementalPCA.html -
KBinsDiscretizer — scikit-learn 1.8.0 doc...
[ 2., 2., 2., 1.], [ 2., 2., 2., 2.]]) Sometimes...>>> X = [[ - 2 , 1 , - 4 , - 1 ], ... [ - 1 , 2 , - 3 , - 0.5...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KBinsDiscretizer.html