General-purpose and introductory examples for the imbalanced-ensemble toolbox.

The examples gallery is still under construction. Please refer to APIs for more detailed guidelines of how to use imbalanced_ensemble.

Basic usage examples

Quick start with imbalanced_ensemble.

Visualize an ensemble classifier

Customize ensemble training log

Train and predict with an ensemble classifier

Classification examples

Examples about using classification algorithms in imbalanced_ensemble.ensemble module.

Classify class-imbalanced hand-written digits

Plot probabilities with different base classifiers

Customize cost matrix

Use dynamic resampling schedule

Classifier comparison

Customize resampling target

Dataset examples

Examples concerning the imbalanced_ensemble.datasets module.

Generate an imbalanced dataset

Make a dataset class-imbalanced

Make digits dataset class-imbalanced

Evaluation examples

Examples illustrating how classification using imbalanced dataset can be done.

Evaluate classification by compiling a report

Metrics specific to imbalanced learning

Pipeline examples

Example of how to use the a pipeline to include under-sampling with scikit-learn estimators.

Usage of pipeline embedding samplers

Visualizer examples

Examples concerning the imbalanced_ensemble.visualizer. module.

Plot confusion matrix

Plot performance curves