- Sort Score
- Result 10 results
- Languages All
- Labels All
Results 311 - 320 of 1,825 for document (0.77 sec)
-
sklearn.tree — scikit-learn 1.5.2 documentation
Decision tree based models for classification and regression. User guide. See the Decision Trees section for further details. Exporting: Plotting:scikit-learn.org/stable/api/sklearn.tree.html -
sklearn.utils — scikit-learn 1.5.2 documentation
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/stable/api/sklearn.utils.html -
process_routing — scikit-learn 1.5.2 documentation
Gallery examples: Metadata Routingscikit-learn.org/stable/modules/generated/sklearn.utils.metadata_routing.process_routing.html -
euclidean_distances — scikit-learn 1.5.2 docume...
Skip to main content Back to top Ctrl + K GitHub euclidean_distances # sklearn.metrics.pairwise. euclidean_distances ...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.euclidean_distances.html -
sklearn.neighbors — scikit-learn 1.5.2 document...
The k-nearest neighbors algorithms. User guide. See the Nearest Neighbors section for further details.scikit-learn.org/stable/api/sklearn.neighbors.html -
spectral_clustering — scikit-learn 1.5.2 docume...
Gallery examples: Segmenting the picture of greek coins in regions Spectral clustering for image segmentationscikit-learn.org/stable/modules/generated/sklearn.cluster.spectral_clustering.html -
make_scorer — scikit-learn 1.5.2 documentation
Gallery examples: Release Highlights for scikit-learn 1.5 Features in Histogram Gradient Boosting Trees Prediction Intervals for Gradient Boosting Regression Lagged features for time series forecas...scikit-learn.org/stable/modules/generated/sklearn.metrics.make_scorer.html -
Gradient Boosting regularization — scikit-learn...
Illustration of the effect of different regularization strategies for Gradient Boosting. The example is taken from Hastie et al 2009 1. The loss function used is binomial deviance. Regularization v...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_regularization.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 -
hinge_loss — scikit-learn 1.5.2 documentation
Gallery examples: Plot classification boundaries with different SVM Kernelsscikit-learn.org/stable/modules/generated/sklearn.metrics.hinge_loss.html