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NuSVR — scikit-learn 1.5.2 documentation
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...for Support Vector Machines [ 2 ] Platt, John (1999). “Probabilistic...scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVR.html -
Feature agglomeration vs. univariate selection ...
selection # This example compares 2 dimensionality reduction strategies:.... randn ( n_samples , size ** 2 ) for x in X : # smooth data x...scikit-learn.org/stable/auto_examples/cluster/plot_feature_agglomeration_vs_univariate_selection.... -
MDS — scikit-learn 1.5.2 documentation
MDS ( n_components = 2 , * , metric = True , n_init =...Parameters : n_components int, default=2 Number of dimensions in which...scikit-learn.org/stable/modules/generated/sklearn.manifold.MDS.html -
ExtraTreesRegressor — scikit-learn 1.5.2 docume...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...= None , min_samples_split = 2 , min_samples_leaf = 1 , min_...scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesRegressor.html -
MultiOutputRegressor — scikit-learn 1.5.2 docum...
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...coefficient of determination \(R^2\) is defined as \((1 - \frac{u}{v})\)...scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html -
CountVectorizer — scikit-learn 1.5.2 documentation
2) means unigrams and bigrams, and (2, 2) means only...= 'word' , ngram_range = ( 2 , 2 )) >>> X2 = vectorizer2 . fit_transform...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html -
PartialDependenceDisplay — scikit-learn 1.5.2 d...
2 Release Highlights for scikit-learn 1.2 Release Highlights...‘both’) is not a valid option for 2-ways interactions plot. As a result,...scikit-learn.org/stable/modules/generated/sklearn.inspection.PartialDependenceDisplay.html -
r2_score — scikit-learn 1.5.2 documentation
y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 ] >>> r2_score...y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 + 1e-8...scikit-learn.org/stable/modules/generated/sklearn.metrics.r2_score.html -
SGDClassifier — scikit-learn 1.5.2 documentation
[ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>> Y = np...np . array ([ 1 , 1 , 2 , 2 ]) >>> # Always scale the input. The...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html -
SGDOneClassSVM — scikit-learn 1.5.2 documentation
[ - 2 , - 1 ], [ 1 , 1 ], [ 2 , 1 ]]) >>> clf =...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDOneClassSVM.html