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Nearest Neighbors regression — scikit-learn 1.5...
Demonstrate the resolution of a regression problem using a k-Nearest Neighbor and the interpolation of the target using both barycenter and constant weights. Generate sample data: Here we generate ...scikit-learn.org/stable/auto_examples/neighbors/plot_regression.html -
Plot classification probability — scikit-learn ...
Plot the classification probability for different classifiers. We use a 3 class dataset, and we classify it with a Support Vector classifier, L1 and L2 penalized logistic regression (multinomial mu...scikit-learn.org/stable/auto_examples/classification/plot_classification_probability.html -
Decision Tree Regression — scikit-learn 1.5.2 d...
A 1D regression with decision tree. The decision trees is used to fit a sine curve with addition noisy observation. As a result, it learns local linear regressions approximating the sine curve. We ...scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html -
confusion_matrix — scikit-learn 1.5.2 documenta...
Gallery examples: Release Highlights for scikit-learn 1.5 Visualizations with Display Objects Post-tuning the decision threshold for cost-sensitive learning Label Propagation digits active learningscikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
export_text — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub export_text # sklearn.tree. export_text ( decision_tree , * , featur...scikit-learn.org/stable/modules/generated/sklearn.tree.export_text.html -
sklearn.utils — scikit-learn 1.7.dev0 documenta...
Various utilities to help with development. Developer guide. See the Utilities for Developers section for further details. Input and parameter validation: Functions to validate input and parameters...scikit-learn.org/dev/api/sklearn.utils.html -
f1_score — scikit-learn 1.5.2 documentation
Gallery examples: Probability Calibration curves Precision-Recall Semi-supervised Classification on a Text Datasetscikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html -
sklearn.decomposition — scikit-learn 1.5.2 docu...
Matrix decomposition algorithms. These include PCA, NMF, ICA, and more. Most of the algorithms of this module can be regarded as dimensionality reduction techniques. User guide. See the Decomposing...scikit-learn.org/stable/api/sklearn.decomposition.html -
kmeans_plusplus — scikit-learn 1.5.2 documentation
Gallery examples: An example of K-Means++ initializationscikit-learn.org/stable/modules/generated/sklearn.cluster.kmeans_plusplus.html -
pairwise_kernels — scikit-learn 1.5.2 documenta...
Skip to main content Back to top Ctrl + K GitHub pairwise_kernels # sklearn.metrics.pairwise. pairwise_kernels ( X , ...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.pairwise_kernels.html