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7. Dataset loading utilities — scikit-learn 1.5...
1. Toy datasets 7.1.1. Iris plants dataset 7.1.2. Diabetes...digits dataset 7.1.4. Linnerrud dataset 7.1.5. Wine recognition dataset...scikit-learn.org/stable/datasets.html -
Gaussian processes on discrete data structures ...
array ([ 1.0 , 1.0 , 2.0 , 2.0 , 3.0 , 3.0 ])...( len ( X_train )), [ 1.0 if c else - 1.0 for c in Y_train ],...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_on_structured_data.html -
Plot randomly generated multilabel dataset — sc...
1 ], color = COLORS . take (( Y * [ 1 , 2 , 4 ]) ...., n_labels = 1 ) ax1 . set_title ( "n_labels=1, length=50" )...scikit-learn.org/stable/auto_examples/datasets/plot_random_multilabel_dataset.html -
additive_chi2_kernel — scikit-learn 1.5.2 docum...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...additive_chi2_kernel ( X , Y ) array([[-1., -2.], [-2., -1.]]) On this page Show...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.additive_chi2_kernel.html -
Plot randomly generated classification dataset ...
n_informative = 1 , n_clusters_per_class = 1 ) plt . scatter...n_clusters_per_class = 1 ) plt . scatter ( X1 [:, 0 ], X1 [:, 1 ], marker...scikit-learn.org/stable/auto_examples/datasets/plot_random_dataset.html -
balanced_accuracy_score — scikit-learn 1.5.2 do...
1 , 0 , 0 , 1 , 0 ] >>> y_pred = [ 0 , 1 , 0 , 0 ,...each class. The best value is 1 and the worst value is 0 when...scikit-learn.org/stable/modules/generated/sklearn.metrics.balanced_accuracy_score.html -
cohen_kappa_score — scikit-learn 1.5.2 document...
which is a number between -1 and 1. The maximum value means complete...function computes Cohen’s kappa [1] , a score that expresses the...scikit-learn.org/stable/modules/generated/sklearn.metrics.cohen_kappa_score.html -
zero_one_loss — scikit-learn 1.5.2 documentation
1 ], [ 1 , 1 ]]), np . ones (( 2 , 2...zero_one_loss >>> y_pred = [ 1 , 2 , 3 , 4 ] >>> y_true = [ 2...scikit-learn.org/stable/modules/generated/sklearn.metrics.zero_one_loss.html -
Plot multi-class SGD on the iris dataset — scik...
feature_names [ 1 ], ) plt . axis ( "tight" ) #...scatter ( X [ idx , 0 ], X [ idx , 1 ], c = color , label = iris ....scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html -
Pixel importances with a parallel forest of tre...
-1 means use all available cores. n_jobs = - 1 Load the...RandomForestClassifi(n_estimators=750, n_jobs=-1, random_state=42) In a Jupyter...scikit-learn.org/stable/auto_examples/ensemble/plot_forest_importances_faces.html