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Vector Quantization Example — scikit-learn 1.5....
This example shows how one can use KBinsDiscretizer to perform vector quantization on a set of toy image, the raccoon face. Original image: We start by loading the raccoon face image from SciPy. We...scikit-learn.org/stable/auto_examples/cluster/plot_face_compress.html -
Caching nearest neighbors — scikit-learn 1.5.2 ...
This examples demonstrates how to precompute the k nearest neighbors before using them in KNeighborsClassifier. KNeighborsClassifier can compute the nearest neighbors internally, but precomputing t...scikit-learn.org/stable/auto_examples/neighbors/plot_caching_nearest_neighbors.html -
fetch_covtype — scikit-learn 1.5.2 documentation
Gallery examples: Release Highlights for scikit-learn 0.24 Scalable learning with polynomial kernel approximation Evaluation of outlier detection estimatorsscikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_covtype.html -
Orthogonal Matching Pursuit — scikit-learn 1.5....
Using orthogonal matching pursuit for recovering a sparse signal from a noisy measurement encoded with a dictionary Total running time of the script:(0 minutes 0.203 seconds) Launch binder Launch J...scikit-learn.org/stable/auto_examples/linear_model/plot_omp.html -
Plotting Validation Curves — scikit-learn 1.5.2...
In this plot you can see the training scores and validation scores of an SVM for different values of the kernel parameter gamma. For very low values of gamma, you can see that both the training sco...scikit-learn.org/stable/auto_examples/model_selection/plot_validation_curve.html -
empirical_covariance — scikit-learn 1.5.2 docum...
Gallery examples: Shrinkage covariance estimation: LedoitWolf vs OAS and max-likelihoodscikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html -
affinity_propagation — scikit-learn 1.5.2 docum...
Gallery examples: Visualizing the stock market structurescikit-learn.org/stable/modules/generated/sklearn.cluster.affinity_propagation.html -
sklearn.compose — scikit-learn 1.5.2 documentation
Meta-estimators for building composite models with transformers. In addition to its current contents, this module will eventually be home to refurbished versions of Pipeline and FeatureUnion. User ...scikit-learn.org/stable/api/sklearn.compose.html -
f_regression — scikit-learn 1.5.2 documentation
Gallery examples: Feature agglomeration vs. univariate selection Comparison of F-test and mutual informationscikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_regression.html -
sklearn.base — scikit-learn 1.5.2 documentation
Base classes for all estimators and various utility functions.scikit-learn.org/stable/api/sklearn.base.html