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Label Propagation digits: Demonstrating perform...
RandomState ( 2 ) indices = np . arange ( len...1.00 1.00 27 1 0.82 1.00 0.90 37 2 1.00 0.86 0.92 28 3 1.00 0.80...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits.html -
Non-negative least squares — scikit-learn 1.7.2...
In this example, we fit a linear model with positive constraints on the regression coefficients and compare the estimated coefficients to a classic linear regression. Generate some random data Spli...scikit-learn.org/stable/auto_examples/linear_model/plot_nnls.html -
clear_data_home — scikit-learn 1.7.2 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version clear_data_home # sklearn.datasets. clear_data_home (...scikit-learn.org/stable/modules/generated/sklearn.datasets.clear_data_home.html -
sklearn.discriminant_analysis — scikit-learn 1....
Linear and quadratic discriminant analysis. User guide. See the Linear and Quadratic Discriminant Analysis section for further details.scikit-learn.org/stable/api/sklearn.discriminant_analysis.html -
calinski_harabasz_score — scikit-learn 1.7.2 do...
Skip to main content Back to top Ctrl + K GitHub Choose version calinski_harabasz_score # sklearn.metrics. calinski_h...scikit-learn.org/stable/modules/generated/sklearn.metrics.calinski_harabasz_score.html -
compute_class_weight — scikit-learn 1.7.2 docum...
Skip to main content Back to top Ctrl + K GitHub Choose version compute_class_weight # sklearn.utils.class_weight. co...scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_class_weight.html -
make_column_selector — scikit-learn 1.7.2 docum...
Gallery examples: Column Transformer with Mixed Types Categorical Feature Support in Gradient Boosting Combine predictors using stacking Evaluation of outlier detection estimatorsscikit-learn.org/stable/modules/generated/sklearn.compose.make_column_selector.html -
sklearn.linear_model — scikit-learn 1.7.2 docum...
A variety of linear models. User guide. See the Linear Models section for further details. The following subsections are only rough guidelines: the same estimator can fall into multiple categories,...scikit-learn.org/stable/api/sklearn.linear_model.html -
sklearn.semi_supervised — scikit-learn 1.7.2 do...
Semi-supervised learning algorithms. These algorithms utilize small amounts of labeled data and large amounts of unlabeled data for classification tasks. User guide. See the Semi-supervised learnin...scikit-learn.org/stable/api/sklearn.semi_supervised.html -
sklearn.cross_decomposition — scikit-learn 1.7....
Algorithms for cross decomposition. User guide. See the Cross decomposition section for further details.scikit-learn.org/stable/api/sklearn.cross_decomposition.html