A toolkit for extracting comprehensible rules from tree-based algorithms
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Updated
Dec 15, 2018 - Jupyter Notebook
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
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
C++ Implementation of Apriori Algorithm in Transactional Databases
Interesting Rule Induction Module with Handling Missing Attributes Values
Demonstration of mining symbolic rules to explain lung cancer treatments
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.
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…
This repository reproduces the experiments of the paper "Discovering outstanding subgroup lists for numeric targets using MDL" published at ECML-PKDD.
Association Rule Mining and SFS
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