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load_svmlight_files — scikit-learn 1.7.2 docume...
shape[1] == X_test.shape[1]). This may not be the...query_id=False , offset=0 , length=-1 ) [source] # Load dataset from...scikit-learn.org/stable/modules/generated/sklearn.datasets.load_svmlight_files.html -
User Guide — scikit-learn 1.7.2 documentation
Guide # 1. Supervised learning 1.1. Linear Models 1.1.1. Ordinary...Lasso 1.1.4. Multi-task Lasso 1.1.5. Elastic-Net 1.1.6. Multi-task...scikit-learn.org/stable/user_guide.html -
sklearn.datasets — scikit-learn 1.7.2 documenta...
make_friedman1 Generate the "Friedman #1" regression problem. make_friedman2...scikit-learn.org/stable/api/sklearn.datasets.html -
StratifiedKFold — scikit-learn 1.7.2 documentation
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]])...>>> y = np . array ([ 0 , 0 , 1 , 1 ]) >>> skf = StratifiedKFold...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedKFold.html -
export_graphviz — scikit-learn 1.7.2 documentation
“x[1]”, …). class_names array-like...scikit-learn.org/stable/modules/generated/sklearn.tree.export_graphviz.html -
graphical_lasso — scikit-learn 1.7.2 documentation
05 ) >>> emp_cov array([[ 1.687, 0.212, -0.209], [ 0.212,...scikit-learn.org/stable/modules/generated/sklearn.covariance.graphical_lasso.html -
IsolationForest — scikit-learn 1.7.2 documentation
1 ], [ 0 ], [ 90 ]]) array([ 1, 1, -1]) For an example...from 0.1 to 'auto' . max_features int or float, default=1.0 The...scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html -
Monotonic Constraints — scikit-learn 1.7.2 docu...
monotonic_cst = { "f_0" : 1 , "f_1" : - 1 } ) . fit ( X_df , y )...) f_1 = rng . rand ( n_samples ) X = np . c_ [ f_0 , f_1 ] noise...scikit-learn.org/stable/auto_examples/ensemble/plot_monotonic_constraints.html -
BernoulliRBM — scikit-learn 1.7.2 documentation
1 , 1 ], [ 1 , 0 , 1 ], [ 1 , 1 , 1 ]]) >>> model...= 256 , * , learning_rate = 0.1 , batch_size = 10 , n_iter = 10...scikit-learn.org/stable/modules/generated/sklearn.neural_network.BernoulliRBM.html -
Visualizing the probabilistic predictions of a ...
uniform ( low =- 1 , high = 1 , size = ( n_samples , 2...> 0 , xor [ "Feature #1" ] + noise [:, 1 ] > 0 ) X = xor [ feature_names...scikit-learn.org/stable/auto_examples/ensemble/plot_voting_decision_regions.html