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Hierarchical clustering: structured vs unstruct...
Example builds a swiss roll dataset and runs hierarchical clustering on their position. For more information, see Hierarchical clustering. In a first step, the hierarchical clustering is performed ...scikit-learn.org/stable/auto_examples/cluster/plot_ward_structured_vs_unstructured.html -
Comparison of the K-Means and MiniBatchKMeans c...
We want to compare the performance of the MiniBatchKMeans and KMeans: the MiniBatchKMeans is faster, but gives slightly different results (see Mini Batch K-Means). We will cluster a set of data, fi...scikit-learn.org/stable/auto_examples/cluster/plot_mini_batch_kmeans.html -
MNIST classification using multinomial logistic...
Here we fit a multinomial logistic regression with L1 penalty on a subset of the MNIST digits classification task. We use the SAGA algorithm for this purpose: this a solver that is fast when the nu...scikit-learn.org/stable/auto_examples/linear_model/plot_sparse_logistic_regression_mnist.html -
Gaussian Processes regression: basic introducto...
A simple one-dimensional regression example computed in two different ways: A noise-free case, A noisy case with known noise-level per datapoint. In both cases, the kernel’s parameters are estimate...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpr_noisy_targets.html -
adjusted_mutual_info_score — scikit-learn 1.5.2...
Gallery examples: A demo of K-Means clustering on the handwritten digits data Adjustment for chance in clustering performance evaluation Demo of DBSCAN clustering algorithm Demo of affinity propaga...scikit-learn.org/stable/modules/generated/sklearn.metrics.adjusted_mutual_info_score.html -
d2_absolute_error_score — scikit-learn 1.5.2 do...
Skip to main content Back to top Ctrl + K GitHub d2_absolute_error_score # sklearn.metrics. d2_absolute_error_score (...scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_absolute_error_score.html -
Early stopping in Gradient Boosting — scikit-le...
Gradient Boosting is an ensemble technique that combines multiple weak learners, typically decision trees, to create a robust and powerful predictive model. It does so in an iterative fashion, wher...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_early_stopping.html -
Agglomerative clustering with different metrics...
Demonstrates the effect of different metrics on the hierarchical clustering. The example is engineered to show the effect of the choice of different metrics. It is applied to waveforms, which can b...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering_metrics.html -
A demo of the Spectral Biclustering algorithm —...
This example demonstrates how to generate a checkerboard dataset and bicluster it using the SpectralBiclustering algorithm. The spectral biclustering algorithm is specifically designed to cluster d...scikit-learn.org/stable/auto_examples/bicluster/plot_spectral_biclustering.html -
Sparse inverse covariance estimation — scikit-l...
Using the GraphicalLasso estimator to learn a covariance and sparse precision from a small number of samples. To estimate a probabilistic model (e.g. a Gaussian model), estimating the precision mat...scikit-learn.org/stable/auto_examples/covariance/plot_sparse_cov.html