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

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

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

Implementation of data typology for imbalanced datasets.

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

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.

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.

Meta learning framework based on rough set measures

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

Rough set class library for machine learning

Geometric concept data generator for testing classification algorithms

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