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Visualizations with Display Objects — scikit-le...
Documentation for Pipeline i Fitted Parameters...False StandardScaler ? Documentation for StandardScaler Parameters...scikit-learn.org/stable/auto_examples/miscellaneous/plot_display_object_visualization.html -
7.3. Preprocessing data — scikit-learn 1.8.0 do...
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 1.8.0 do...
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 -
Demo of OPTICS clustering algorithm — scikit-le...
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 — scikit...
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 -
SGD: convex loss functions — scikit-learn 1.8.0...
A plot that compares the various convex loss functions supported by SGDClassifier. Total running time of the script:(0 minutes 0.086 seconds) Launch binder Launch JupyterLite Download Jupyter noteb...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_loss_functions.html -
Robust linear estimator fitting — scikit-learn ...
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 -
Plotting Cross-Validated Predictions — scikit-l...
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 -
1.10. Decision Trees — scikit-learn 1.8.0 docum...
Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning s...scikit-learn.org/stable/modules/tree.html