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Lagged features for time series forecasting — s...
1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1" "quantile 5"..."39.9 ± 3.2" "17.1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1" "quantile 95"...scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html -
Column Transformer with Mixed Types — scikit-le...
versionadded:: 1.0 .. versionchanged:: 1.6 `verbose_feature_names_out`..... versionadded:: 1.5 .. versionchanged:: 1.7 The default value...scikit-learn.org/stable/auto_examples/compose/plot_column_transformer_mixed_types.html -
Version 0.22 — scikit-learn 1.8.0 documentation
is given for both n_jobs=1 or n_jobs>1 both with shared memory...results between n_jobs=1 and n_jobs>1 due to the handling of...scikit-learn.org/stable/whats_new/v0.22.html -
SVM Tie Breaking Example — scikit-learn 1.8.0 d...
1 ] . min (), X [:, 1 ] . max ()] xs = np...xlim [ 1 ], 1000 ) ys = np . linspace ( ylim [ 0 ], ylim [ 1 ], 1000...scikit-learn.org/stable/auto_examples/svm/plot_svm_tie_breaking.html -
Understanding the decision tree structure — sci...
[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...[{0: 1, 1: 1}, {0: 1, 1: 5}, {0: 1, 1: 1}, {0: 1, 1: 1}] instead...scikit-learn.org/stable/auto_examples/tree/plot_unveil_tree_structure.html -
7.4. Imputation of missing values — scikit-lear...
array ([[ - 1 , - 1 , 1 , 3 ], ... [ 4 , - 1 , 0 , - 1 ], ... [...= sp . csc_matrix ([[ 1 , 2 ], [ 0 , - 1 ], [ 8 , 4 ]]) >>> imp...scikit-learn.org/stable/modules/impute.html -
Developing scikit-learn estimators — scikit-lea...
SGDClassifier ([[ 1 , 2 ], [ 2 , 3 ]], [ - 1 , 1 ]) # WRONG! Ideally,...be modified if param1 > 1 : param2 += 1 self . param1 = param1...scikit-learn.org/stable/developers/develop.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 -
Multiclass sparse logistic regression on 20newg...
accuracies = [ 1 / n_classes ] times = [ 0 ] densities = [ 1 ] model_params...model_params [ "iters" ][ - 1 ], model , times [ - 1 ]) ) fig = plt . figure...scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_20newsgroups.html -
Frequently Asked Questions — scikit-learn 1.8.0...
reshape ( - 1 , 1 ) >>> X array([[0], [1], [2]]) >>> # We...'brute' ) (array([0, 1]), array([ 0, 0, -1])) Note that the example...scikit-learn.org/stable/faq.html