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Examples of Using FrozenEstimator — scikit-lear...
data points: [[0.18 0.82] [0.29 0.71] [0. 1. ]] Predicted class...FixedThresholdClassi: [[0.18 0.82] [0.29 0.71] [0. 1. ]] Predicted class...scikit-learn.org/stable/auto_examples/frozen/plot_frozen_examples.html -
Dimensionality Reduction with Neighborhood Comp...
= [( "PCA" , pca ), ( "LDA" , lda ), ( "NCA" , nca )] # plt.figure()...dim_reduction_methods ): plt . figure () # plt.subplot(1, 3, i + 1, aspect=1) #...scikit-learn.org/stable/auto_examples/neighbors/plot_nca_dim_reduction.html -
PassiveAggressiveClassifier — scikit-learn 1.7....
n_samples / (n_classes * np.bincount(y)) . Added in version 0.17: parameter...sklearn.linear_model. PassiveAggressiveCla ( * , C = 1.0 , fit_intercept...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PassiveAggressiveClassifier.html -
PassiveAggressiveRegressor — scikit-learn 1.7.1...
[-0.02306214] >>> print ( regr . predict ([[ 0 , 0 , 0 , 0 ]]))...PassiveAggressiveReg ( max_iter = 100 , random_state = 0 , ... tol = 1e-3 ) >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PassiveAggressiveRegressor.html -
lasso_path — scikit-learn 1.7.1 documentation
, 2 , 3.1 ], [ 2.3 , 5.4 , 4.3 ]]) . T >>> y = np . array ([...1. , .5 ]) >>> print ( coef_path ) [[0. 0. 0.46874778] [0.2159048...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lasso_path.html -
lars_path_gram — scikit-learn 1.7.1 documentation
array([[ 0. , 0. , 0. ], [ 0. , 0. , 0. ], [ 0. , 0. , 0. ], [...random_state = 0 ... ) >>> true_coef array([ 0. , 0. , 0. , 97.9, 45.7])...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path_gram.html -
ensemble.rst.txt
Gradient Boosting ---------- Scikit-learn 0.21 introduced two...HistGradientBoosting(max_iter=100).fit(X_train, y_train) >>> clf.score(X_test,...scikit-learn.org/stable/_sources/modules/ensemble.rst.txt -
sklearn.gaussian_process — scikit-learn 1.7.1 d...
kernels \(k_1\) and \(k_2\) and combines them via kernels.RBF Radial...kernels.DotProduct Dot-Product kernel. kernels.ExpSineSquared Exp-Sine-Squared...scikit-learn.org/stable/api/sklearn.gaussian_process.html -
sklearn.cross_decomposition — scikit-learn 1.7....
tion # Algorithms for cross decomposition. User guide. See the...details. CCA Canonical Correlation Analysis, also known as "Mode...scikit-learn.org/stable/api/sklearn.cross_decomposition.html -
Release Highlights for scikit-learn 1.6 — sciki...
, 1 , 6 , np . nan ]) . reshape ( - 1 , 1 ) y = [ 0 , 0 , 1 ,...fit ( X , y ) forest . predict ( X ) array([0, 0, 1, 1]) Download...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_6_0.html