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12. Dispatching — scikit-learn 1.7.2 documentation
Array API support (experimental)- Example usage, Support for Array API-compatible inputs, Input and output array type handling, Common estimator checks..scikit-learn.org/stable/dispatching.html -
5. Inspection — scikit-learn 1.7.2 documentation
Predictive performance is often the main goal of developing machine learning models. Yet summarizing performance with an evaluation metric is often insufficient: it assumes that the evaluation metr...scikit-learn.org/stable/inspection.html -
sklearn.metrics — scikit-learn 1.7.2 documentation
Score functions, performance metrics, pairwise metrics and distance computations. User guide. See the Metrics and scoring: quantifying the quality of predictions and Pairwise metrics, Affinities an...scikit-learn.org/stable/api/sklearn.metrics.html -
fbeta_score — scikit-learn 1.7.2 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version fbeta_score # sklearn.metrics. fbeta_score ( y_true ,...scikit-learn.org/stable/modules/generated/sklearn.metrics.fbeta_score.html -
ndcg_score — scikit-learn 1.7.2 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version ndcg_score # sklearn.metrics. ndcg_score ( y_true , y...scikit-learn.org/stable/modules/generated/sklearn.metrics.ndcg_score.html -
max_error — scikit-learn 1.7.2 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version max_error # sklearn.metrics. max_error ( y_true , y_p...scikit-learn.org/stable/modules/generated/sklearn.metrics.max_error.html -
Kernel Density Estimation — scikit-learn 1.7.2 ...
This example shows how kernel density estimation (KDE), a powerful non-parametric density estimation technique, can be used to learn a generative model for a dataset. With this generative model in ...scikit-learn.org/stable/auto_examples/neighbors/plot_digits_kde_sampling.html -
SVM with custom kernel — scikit-learn 1.7.2 doc...
Simple usage of Support Vector Machines to classify a sample. It will plot the decision surface and the support vectors. Total running time of the script:(0 minutes 0.090 seconds) Launch binder Lau...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
sklearn.preprocessing — scikit-learn 1.7.2 docu...
Methods for scaling, centering, normalization, binarization, and more. User guide. See the Preprocessing data section for further details.scikit-learn.org/stable/api/sklearn.preprocessing.html -
get_scorer — scikit-learn 1.7.2 documentation
Gallery examples: Release Highlights for scikit-learn 1.4scikit-learn.org/stable/modules/generated/sklearn.metrics.get_scorer.html