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sklearn.model_selection — scikit-learn 1.8.0 do...
Tools for model selection, such as cross validation and hyper-parameter tuning. User guide. See the Cross-validation: evaluating estimator performance, Tuning the hyper-parameters of an estimator, ...scikit-learn.org/stable/api/sklearn.model_selection.html -
sklearn.feature_selection — scikit-learn 1.8.0 ...
Feature selection algorithms. These include univariate filter selection methods and the recursive feature elimination algorithm. User guide. See the Feature selection section for further details.scikit-learn.org/stable/api/sklearn.feature_selection.html -
sklearn.neural_network — scikit-learn 1.8.0 doc...
Models based on neural networks. User guide. See the Neural network models (supervised) and Neural network models (unsupervised) sections for further details.scikit-learn.org/stable/api/sklearn.neural_network.html -
sklearn.experimental — scikit-learn 1.8.0 docum...
Importable modules that enable the use of experimental features or estimators.scikit-learn.org/stable/api/sklearn.experimental.html -
sklearn.exceptions — scikit-learn 1.8.0 documen...
Custom warnings and errors used across scikit-learn.scikit-learn.org/stable/api/sklearn.exceptions.html -
3.2. Tuning the hyper-parameters of an estimato...
coupling parameters from a text documents feature extractor (n-gram...scikit-learn.org/stable/modules/grid_search.html -
org.springframework.web.servlet.view.document C...
document Package Hierarchies: All Packages...org.springframework.web.servlet.view.document. AbstractPdfView org.spri...docs.spring.io/spring-framework/docs/current/javadoc-api/org/springframework/web/servlet/view/doc... -
sklearn.random_projection — scikit-learn ...
Random projection transformers. Random projections are a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional ...scikit-learn.org/stable/api/sklearn.random_projection.html -
Compare BIRCH and MiniBatchKMeans — scikit-lear...
This example compares the timing of BIRCH (with and without the global clustering step) and MiniBatchKMeans on a synthetic dataset having 25,000 samples and 2 features generated using make_blobs. B...scikit-learn.org/stable/auto_examples/cluster/plot_birch_vs_minibatchkmeans.html -
Semi Supervised Classification — scikit-learn 1...
Examples concerning the sklearn.semi_supervised module. Decision boundary of semi-supervised classifiers versus SVM on the Iris dataset Effect of varying threshold for self-training Label Propagati...scikit-learn.org/stable/auto_examples/semi_supervised/index.html