A toolkit for extracting comprehensible rules from tree-based algorithms

Knowledge Graph summarization for anomaly/error detection & completion (WebConf '20)

Comparison of Apriori and FP-Growth Algorithm in accuracy metrics, execution time and memory usage for a prediction system of dengue.

RDFRules: Analytical Tool for Rule Mining from RDF Knowledge Graphs

AMIE+ association rule mining

Instance Neighbouring by using Knowledge

A Python package for process-mining with DECLARE models.

📯 Knowledge Discovery in RDF Datasets using SPARQL Queries.

Source code accompanying our paper 'Multi-Directional Rule Set Learning', Discovery Science 2020.

Interpret all the models - a genetic optimization approach to model agnostic black box explanations based on MAGIX.

VICKEY: Mining Conditional Keys on RDF Knowledge Bases

Interesting Rule Induction Module with Handling Missing Attributes Values

Mining symbolic rules over knowledge graphs

C++ Implementation of Apriori Algorithm in Transactional Databases

IREP implementation - Data Mining course project

Demonstration of mining symbolic rules to explain lung cancer treatments

A TS-based tool to explain possible biases in datasets where the target-variable is numeric.

Customer Segmentation Analysis, developed using Python, by using Clustering Algorithm for the purpose of dividing the customers into groups based on the similarity in different ways that are relevant to marketing such as location, items, spending score, salary and accordingly identify customers’ behavior and interests and focus on them for futur…

Python wrapper for the graph rule mining tool RDFRules.

NEON mines rules for detecting natural language patterns in software informal documents. The inferred rules can be used for identifying and extracting relevant information embedded in unstructured texts.