A library of extension and helper modules for Python's data analysis and machine learning libraries.

An efficient Python implementation of the Apriori algorithm.

Mining Association Rules and Frequent Itemsets with R

Association rule mining is a technique to identify underlying relations between different items.

🍊 📦 Frequent itemsets and association rules mining for Orange 3.

Visualizing Association Rules and Frequent Itemsets with R

Classification Based on Association Rules in R

Association Rule Mining from Spatial Data for Crime Analysis

采用Apriori算法,Fpgrowth算法,Eclat算法对超市商品数据集进行频繁集与关联规则的挖掘

Implementation of FPTree-Growth and Apriori-Algorithm for finding frequent patterns in Transactional Database.

Implement Frequent Itemset Mining Program in Python

Time series prediction and text analysis using Keras LSTM, plus clustering, association rules mining

个性化推荐模型，主要包括als、als_wr、biaslfm、lfm、nmf、svdpp、基于内容、基于内容回归、user-cf、item-cf、slopeone、关联规则以及基于内容和cf的混合等模型。

A Java implementation of the Apriori algorithm for finding frequent item sets and (optionally) generating association rules

Arulesviz - interactive association rules vizualization tool for python

RuleMiner is a package for data mining in Julia with support for itemset and association rule mining algorithms

Association rule mining using Apriori algorithm.

赛题一：面向大数据的高高效关联规则推荐算法

Python project for Market Basket Analysis. Generates synthetic retail transactions, mines frequent itemsets using Apriori & FP-Growth, derives association rules, and outputs CSVs + visualizations. Portfolio-ready example demonstrating data science methods for uncovering product co-purchase patterns.

Hadoop MapReduce implementation of Market Basket Analysis for Frequent Item-set and Association Rule mining using Apriori algorithm.