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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 -
LogisticRegressionCV — scikit-learn 1.7.1 docum...
‘l2’ yes ‘newton-cholesky’ ‘l2’, yes ‘sag’ ‘l2’, yes ‘saga’ ‘elasticnet’,...multiclass ‘lbfgs’ ‘l2’ yes ‘liblinear’ ‘l1’, ‘l2’ no ‘newton-cg’ ‘l2’...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html -
ElasticNet — scikit-learn 1.7.1 documentation
linear_model. ElasticNet ( alpha = 1.0 , * , l1_ratio = 0.5 , fit_intercept...n_samples ) * || y - Xw ||^ 2_2 + alpha * l1_ratio * || w || _1 + 0.5...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNet.html -
CalibratedClassifierCV — scikit-learn 1.7.1 doc...
version 1.2. method {‘sigmoid’, ‘isotonic’}, default=’sigmoid’ The...version 0.24. ensemble bool, or “auto”, default=”auto” Determines...scikit-learn.org/stable/modules/generated/sklearn.calibration.CalibratedClassifierCV.html -
LabelBinarizer — scikit-learn 1.7.1 documentation
transform ([ 0 , 1 , 2 , 1 ]) array([[1, 0, 0], [0, 1, 0], [0, 0, 1],...transform ([ 1 , 6 ]) array([[1, 0, 0, 0], [0, 0, 0, 1]]) Binary targets...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelBinarizer.html -
5.2. Permutation feature importance — scikit-le...
+/- 0.050 bmi 0.176 +/- 0.048 bp 0.088 +/- 0.033 sex 0.056 +/- 0.023...+/- { r . importances_std [ i ] : .3f } " ) ... s5 0.204 +/-...scikit-learn.org/stable/modules/permutation_importance.html -
1.15. Isotonic regression — scikit-learn 1.7.1 ...
\hat{y}_j\) whenever \(X_i \le X_j\) , where the weights \(w_i\) are...Ctrl + K GitHub Choose version 1.15. Isotonic regression # The...scikit-learn.org/stable/modules/isotonic.html -
1.12. Multiclass and multioutput algorithms — s...
= np . array ([ 'apple' , 'pear' , 'apple' , 'orange' ]) >>> print...array ([ 'apple' , 'pear' , 'apple' , 'orange' ]) >>> y_dense = LabelBinarizer...scikit-learn.org/stable/modules/multiclass.html -
KNeighborsClassifier — scikit-learn 1.7.1 docum...
KNeighborsClassifier(...) >>> print ( neigh . predict ([[ 1.1 ]])) [0] >>> print...boundary. algorithm {‘auto’, ‘ball_tree’, ‘kd_tree’, ‘brute’}, default=’auto’...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html -
fetch_openml — scikit-learn 1.7.1 documentation
retries. parser {“auto”, “pandas”, “liac-arff”}, default=”auto”...bool = 'auto' , n_retries : int = 3 , delay : float = 1.0 , parser...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_openml.html