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randomized_svd — scikit-learn 1.6.0 documentation
approximation problem described in [1] (problem (1.5), p5). Refer to Wikipedia...n_iter=0 or 1 should even work fine in theory (see [1] page 9)....scikit-learn.org/stable/modules/generated/sklearn.utils.extmath.randomized_svd.html -
det_curve — scikit-learn 1.6.0 documentation
y_true is in {-1, 1} or {0, 1}, pos_label is set to 1, otherwise...labels are not either {-1, 1} or {0, 1}, then pos_label should...scikit-learn.org/stable/modules/generated/sklearn.metrics.det_curve.html -
coverage_error — scikit-learn 1.6.0 documentation
y_true = [[ 1 , 0 , 0 ], [ 0 , 1 , 1 ]] >>> y_score = [[ 1 , 0 , 0...0 ], [ 0 , 1 , 1 ]] >>> coverage_error ( y_true , y_score ) np.float64(1.5)...scikit-learn.org/stable/modules/generated/sklearn.metrics.coverage_error.html -
make_friedman1 — scikit-learn 1.6.0 documentation
Annals of Statistics 19 (1), pages 1-67, 1991. [ 2 ] L. Breiman,...[source] # Generate the “Friedman #1” regression problem. This dataset...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman1.html -
Gradient Boosting regression — scikit-learn 1.6...
subplot ( 1 , 1 , 1 ) plt . title ( "Deviance"...12 , 6 )) plt . subplot ( 1 , 2 , 1 ) plt . barh ( pos , feature_importance...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regression.html -
log_loss — scikit-learn 1.6.0 documentation
p) = -(y \log (p) + (1 - y) \log (1 - p))\] Read more in the..., "spam" ], ... [[ .1 , .9 ], [ .9 , .1 ], [ .8 , .2 ], [ .35...scikit-learn.org/stable/modules/generated/sklearn.metrics.log_loss.html -
dcg_score — scikit-learn 1.6.0 documentation
asarray ([[ 1 , 0 , 0 , 0 , 1 ]]) >>> # by default ties...to have a score between 0 and 1. References Wikipedia entry for...scikit-learn.org/stable/modules/generated/sklearn.metrics.dcg_score.html -
power_transform — scikit-learn 1.6.0 documentation
[[-1.332... -0.707...] [ 0.256... -0.707...] [ 1.076... 1.414...]]...Available methods are: ‘yeo-johnson’ [1] , works with positive and negative...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.power_transform.html -
make_circles — scikit-learn 1.6.0 documentation
int64(1), np.int64(1), np.int64(1), np.int64(0), np.int64(0)]...outer circle in the range [0, 1) . Returns : X ndarray of shape...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_circles.html -
Importance of Feature Scaling — scikit-learn 1....
0 and 1,000; whereas the variable “hue” varies between 1 and 10....it has a standard deviation of 1 and a mean of 0. Even if tree...scikit-learn.org/stable/auto_examples/preprocessing/plot_scaling_importance.html