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7.2. Feature extraction — scikit-learn 1....
2.0986]}{\sqrt{\big(3^2 + 0^2 + 2.0986^2\big)}} = [...one_image , ( 2 , 2 )) >>> patches . shape (9, 2, 2, 3) >>>...scikit-learn.org/stable/modules/feature_extraction.html -
2.8. Density Estimation — scikit-learn 1....
[ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...the distribution of points. 2.8.2. Kernel Density Estimation #...scikit-learn.org/stable/modules/density.html -
confusion_matrix — scikit-learn 1.7.2 doc...
>>> y_true = [ 2 , 0 , 2 , 2 , 0 , 1 ] >>> y_pred...y_pred = [ 0 , 0 , 2 , 2 , 0 , 2 ] >>> confusion_matrix...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
BaseEstimator — scikit-learn 1.7.2 docume...
{'param': 2} >>> X = np . array ([[ 1 , 2 ], [ 2 , 3 ],...y ) . predict ( X ) array([2, 2, 2]) >>> estimator ....scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html -
kmeans_plusplus — scikit-learn 1.7.2 docu...
2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2 ], [ 10 , 4...array([[10, 2], [ 1, 0]]) >>> indices array([3, 2]) Gallery...scikit-learn.org/stable/modules/generated/sklearn.cluster.kmeans_plusplus.html -
hamming_loss — scikit-learn 1.7.2 documen...
2 , 3 , 4 ] >>> y_true = [ 2 , 2 , 3 , 4 ]...[ 1 , 1 ]]), np . zeros (( 2 , 2 ))) 0.75 Gallery examples #...scikit-learn.org/stable/modules/generated/sklearn.metrics.hamming_loss.html -
johnson_lindenstrauss_min_dim — scikit-le...
v||^2 < ||p(u) - p(v)||^2 < (1 + eps) ||u - v||^2 Where...>= 4 log(n_samples) / (eps^2 / 2 - eps^3 / 3) Note that the number...scikit-learn.org/stable/modules/generated/sklearn.random_projection.johnson_lindenstrauss_min_dim... -
KNeighborsRegressor — scikit-learn 1.7.2 ...
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which...float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsRegressor.html -
mean_pinball_loss — scikit-learn 1.7.2 do...
2 , 3 ] >>> mean_pinball_loss...mean_pinball_loss ( y_true , [ 0 , 2 , 3 ], alpha = 0.1 ) 0.03... >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_pinball_loss.html -
root_mean_squared_error — scikit-learn 1....
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>...>>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.root_mean_squared_error.html