The problexity is an open-source python library containing the implementation of measures describing the complexity of the classification and regression problems.

The data complexity library, DCoL, is a machine learning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.

Alignment-free simulation, computation, and visualization of Low-compexity regions in biological data

The Python Class Overlap Libray (pycol) assembles a comprehensive set of complexity measures associated with the characterization of the Class Overlap problem.

MfeatExtractor is an automated code for meta-feature extraction, useful for meta-learning projects.

Meta learning framework based on rough set measures

A generator of multi-dimensional and multi-class imbalanced data, designed to create artificial datasets for the study of data difficulty factors in imbalanced learning.

Rough set class library for machine learning

A multi-view panorama of Data-Centric AI: Techniques, Tools, and Applications (ECAI Tutorial 2024)

Geometric concept data generator for testing classification algorithms

A large dataset for studying the early readmission of diabetic patients problem

Implementation of data typology for imbalanced datasets.