subgroup-discovery

subgroups is a python library which contains a collection of subgroup discovery algorithms and other data analysis utilities.

A machine learning python package for learning ensembles of subgroups for predictive tasks.

R code for the discovery of COVID-19 subgroups by symptoms and comorbidities.

Code for the papers "Using Constraints to Discover Sparse and Alternative Subgroup Descriptions" and "Subgroup Discovery with Small and Alternative Feature Sets".

A heavily modified Exceptional Preferences Mining version of the Python Exceptional Model Mining implemenation by MathynS supporting both an Apriori as well as a Best First algorithm for mining subgroups featuring exceptional preferences.

This repository reproduces the experiments of the paper "Discovering outstanding subgroup lists for numeric targets using MDL" published at ECML-PKDD.

Redescriptional model mining in python

Análise de Intervenção em Ansiedade com Descoberta de Subgrupos

Subgroup discovery method is applied to random forest in order to select subgroups of entities in the dataset, which seems to be able to approximate with a single random tree. This provides us with the interpretable subgroups of dataset, which makes the random forest model less black-box than usual.

A distributed subgroup discovery framework using Apache Kafka and Zookeeper. Implements the paraDis methodology with a master-worker architecture for scalable and efficient subgroup discovery using the pysubgroup\ library

The Adaptive Local Knockoff Filter

Projeto Final de Aprendizado Descritivo @ DCC/UFMG

Repo for the IDA 2026 Paper: Exceptional Model Residual Mining, and Three Richer EMM Description Languages

Defense presentation for the dissertation "Leveraging Constraints for User-Centric Feature Selection".

Text for the papers "Using Constraints to Discover Sparse and Alternative Subgroup Descriptions" and "Subgroup Discovery with Small and Alternative Feature Sets".

Package containing functions to manage Error Distribution Rules

This Code accompanies the paper "Local Subgroup Discovery on Attributed Network Graphs" which is part of the IDA2025 conference. The conference proceedings are published in Springers Lecture Notes in Computer Science (LNCS).

Text for the dissertation "Leveraging Constraints for User-Centric Feature Selection".