A minimalistic framework for Numerical Association Rule Mining

Analytics and Systems of Big Data

Scalable association rule mining from tabular datasets.

A minimalist machine learning library built from scratch by IFRI AI students to explore and understand core ML algorithms.🇧🇯

"Frequent Mining Algorithms" is a Python library that includes frequent mining algorithms. This library contains popular algorithms used to discover frequent items and patterns in datasets. Frequent mining is widely used in various applications to uncover significant insights, such as market basket analysis, network traffic analysis, etc.

Market Basket Analysis What is it? Market Basket Analysis is a modelling technique based upon the theory that if you buy a certain group of items, you are more (or less) likely to buy another group of items. For example, if you are in an English pub and you buy a pint of beer and don't buy a bar meal, you are more likely to buy crisps (US. chips…

Open-source framework designed to enhance the ESCO taxonomy

A python implementation of the Multiple Support Apriori Algorithm

This project is a Market Basket Analysis App that analyzes customer purchase patterns to generate association rules and offer personalized product recommendations.

Discovering association rules from high dimensional small tabular data via neurosymbolic rule mining supported by fine-tuning using tabular foundation models

implementation of fp_growth algorithm using python3

UG Final Year Project based on Suffix Forest Based Tri-clustering

designing association rule mining model for given data-set using apriori algorithm

Identification, Recommendation, & Ranking of Occupants' Behavioral Energy - Master's Thesis

This is an API implementation of our graduation project "details" using FastAPI

implementation of Apriori algorithm using python3

Codes related to data warehousing and mining

This repository contains HWs of data mining course