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Developing scikit-learn estimators — scikit-lea...
SGDClassifier ([[ 1 , 2 ], [ 2 , 3 ]], [ - 1 , 1 ]) # WRONG! Ideally,...be modified if param1 > 1 : param2 += 1 self . param1 = param1...scikit-learn.org/stable/developers/develop.html -
clone — scikit-learn 1.7.0 documentation
>>> X = [[ - 1 , 0 ], [ 0 , 1 ], [ 0 , - 1 ], [ 1 , 0 ]] >>> y...y = [ 0 , 0 , 1 , 1 ] >>> classifier = LogisticRegression ()...scikit-learn.org/stable/modules/generated/sklearn.base.clone.html -
ARDRegression — scikit-learn 1.7.0 documentation
[ 1 , 1 ], [ 2 , 2 ]], [ 0 , 1 , 2 ]) ARDRegression()...>>> clf . predict ([[ 1 , 1 ]]) array([1.]) fit ( X , y ) [source]...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ARDRegression.html -
Categorical Feature Support in Gradient Boostin...
will need 4 splits: 1 split to isolate A , 1 split to isolate F...include = "number" ) . shape [ 1 ] print ( f "Number of samples:...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_categorical.html -
SkewedChi2Sampler — scikit-learn 1.7.0 document...
[ 1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...SkewedChi2Sampler ( * , skewedness = 1.0 , n_components = 100 , random_state...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.SkewedChi2Sampler.html -
SGDRegressor — scikit-learn 1.7.0 documentation
l1_ratio <= 1. l1_ratio=0 corresponds to L2 penalty, l1_ratio=1 to L1....True , verbose = 0 , epsilon = 0.1 , random_state = None , learning_rate...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDRegressor.html -
mean_poisson_deviance — scikit-learn 1.7.0 docu...
with the power parameter power=1 . Read more in the User Guide...mean_poisson_deviance >>> y_true = [ 2 , 0 , 1 , 4 ] >>> y_pred = [ 0.5 , 0.5...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_poisson_deviance.html -
Release Highlights for scikit-learn 0.22 — scik...
pclass embarked 0 1 S 1 1 S 2 1 S 3 1 S 4 1 S Checking scikit-learn...array ([ 0 , 1 , 2 , np . nan ]) . reshape ( - 1 , 1 ) y = [ 0 ,...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_0_22_0.html -
trustworthiness — scikit-learn 1.7.0 documentation
1]. It is defined as \[T(k) = 1 - \frac{2}{nk (2n...(2n - 3k - 1)} \sum^n_{i=1} \sum_{j \in \mathcal{N}_{i}^{k}}...scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html -
DummyClassifier — scikit-learn 1.7.0 documentation
([ - 1 , 1 , 1 , 1 ]) >>> y = np . array ([ 0 , 1 , 1 , 1 ]) >>>...dummy_clf . predict ( X ) array([1, 1, 1, 1]) >>> dummy_clf . score (...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html