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SVM: Weighted samples — scikit-learn 1.8....
Plot decision function of a weighted dataset, where the size of points is proportional to its weight. The sample weighting rescales the C parameter, which means that the classifier puts more emphas...scikit-learn.org/stable/auto_examples/svm/plot_weighted_samples.html -
Agglomerative clustering with and without struc...
This example shows the effect of imposing a connectivity graph to capture local structure in the data. The graph is simply the graph of 20 nearest neighbors. There are two advantages of imposing a ...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering.html -
7.3. Preprocessing data — scikit-learn 1....
The sklearn.preprocessing package provides several common utility functions and transformer classes to change raw feature vectors into a representation that is more suitable for the downstream esti...scikit-learn.org/stable/modules/preprocessing.html -
1.13. Feature selection — scikit-learn 1....
The classes in the sklearn.feature_selection module can be used for feature selection/dimensionality reduction on sample sets, either to improve estimators’ accuracy scores or to boost their perfor...scikit-learn.org/stable/modules/feature_selection.html -
Demonstrating the different strategies of KBins...
This example presents the different strategies implemented in KBinsDiscretizer: ‘uniform’: The discretization is uniform in each feature, which means that the bin widths are constant in each dimens...scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization_strategies.html -
Plotting Cross-Validated Predictions — sc...
This example shows how to use cross_val_predict together with PredictionErrorDisplay to visualize prediction errors. We will load the diabetes dataset and create an instance of a linear regression ...scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html -
8. Dataset loading utilities — scikit-lea...
The sklearn.datasets package embeds some small toy datasets and provides helpers to fetch larger datasets commonly used by the machine learning community to benchmark algorithms on data that comes ...scikit-learn.org/stable/datasets.html -
Demo of OPTICS clustering algorithm — sci...
Finds core samples of high density and expands clusters from them. This example uses data that is generated so that the clusters have different densities. The OPTICS is first used with its Xi clust...scikit-learn.org/stable/auto_examples/cluster/plot_optics.html -
Tweedie regression on insurance claims — ...
This example illustrates the use of Poisson, Gamma and Tweedie regression on the French Motor Third-Party Liability Claims dataset, and is inspired by an R tutorial 1. In this dataset, each sample ...scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html -
Robust linear estimator fitting — scikit-...
Here a sine function is fit with a polynomial of order 3, for values close to zero. Robust fitting is demonstrated in different situations: No measurement errors, only modelling errors (fitting a s...scikit-learn.org/stable/auto_examples/linear_model/plot_robust_fit.html