Association rule generation using FP Growth algorithm

Data Mining course projects

A number of data mining algorithms implemented using grocery store shopping lists as a working example.

Market Basket Analysis for an organization to identify the most frequently selling products in order to devise cross-selling marketing strategies using Apriori algorithm.

Association rules (with taxonomy) mining

CLM is a new data structure that uses matrices in which data from graph is stored and CLM-Miner is the algorithm that is used to extract MFI from the CLM.

Use Apriori algorithm to calculate frequent itemset from a list of arrarys

⚡️ 📊 A fast multi-threaded implementation of the PaNDa+ algorithm for mining Top-K Binary patterns in transactional data.

A Parallel Implementation of The Apriori Algorithm on AiMOS Supercomputer Using CUDA and MPI

Learning embeddings for transactions via frequent itemsets, Word2Vec, and Doc2Vec

a dice game program that uses every kind of dye like dungeons and dragons

EAFIM: efficient apriori-based frequent itemset mining algorithmon Spark for big transactional data

Projeto Final de Aprendizado Descritivo @ DCC/UFMG

"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.

An Apache Spark implementation of the Apriori algorithm to calculate the frequent item sets and association rules.

Repository for all assignments of the course COL761: Data Mining (Fall 2020), taught at IIT Delhi

Implementation of the apriori algorithm for frequent itemset generation and rule mining

Repository with the source code of our experiments for an automated NLP-based framework to improve test cases written in natural language

Classification Using Frequent Patterns - UEH