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SVR — scikit-learn 1.5.0 documentation
Added in version 1.1. n_support_ ndarray of shape (1,), dtype=int32..., tol = 0.001 , C = 1.0 , epsilon = 0.1 , shrinking = True ,...scikit-learn.org/stable/modules/generated/sklearn.svm.SVR.html -
Putting it all together — scikit-learn 1.5.0 do...
arange ( 1 , pca . n_components_ + 1 ), pca . explained_variance_ratio_...y_pred [ i ]] . rsplit ( " " , 1 )[ - 1 ] true_name = target_names...scikit-learn.org/stable/tutorial/statistical_inference/putting_together.html -
QuantileTransformer — scikit-learn 1.5.0 docume...
Added in version 1.5: The option None to disable...all strings. Added in version 1.0. See also quantile_transform...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.QuantileTransformer.html -
GaussianNB — scikit-learn 1.5.0 documentation
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> Y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html -
IsolationForest — scikit-learn 1.5.0 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 -
MaxAbsScaler — scikit-learn 1.5.0 documentation
-1. , 1. ], [ 1. , 0. , 0. ], [ 0. , 1. , -0.5]]) fit...= [[ 1. , - 1. , 2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , -...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html -
PrecisionRecallDisplay — scikit-learn 1.5.0 doc...
Added in version 1.3. Attributes : line_ matplotlib...not plotted. Added in version 1.3. ax_ matplotlib Axes Axes with...scikit-learn.org/stable/modules/generated/sklearn.metrics.PrecisionRecallDisplay.html -
1.11. Ensembles: Gradient boosting, random fore...
Gradient Boosting models 1.11.1.1.1. Usage # Most of the parameters...= [[ 1 , 0 ], ... [ 1 , 0 ], ... [ 1 , 0 ], ... [ 0 , 1 ]] >>>...scikit-learn.org/stable/modules/ensemble.html -
StratifiedKFold — scikit-learn 1.5.0 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 -
TfidfVectorizer — scikit-learn 1.5.0 documentation
ngram_range=(1 , 1) , max_df=1.0 , min_df=1 , max_features=None...ngram_range of (1, 1) means only unigrams, (1, 2) means unigrams...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.TfidfVectorizer.html