Some experiments about Machine Learning

Implementation of the Apriori and Eclat algorithms, two of the best-known basic algorithms for mining frequent item sets in a set of transactions, implementation in Python.

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.

赛题一：面向大数据的高高效关联规则推荐算法

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

FPGrowth Algorithm implementation in TypeScript / JavaScript.

Analytics and Systems of Big Data

"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.

fim is a collection of some popular frequent itemset mining algorithms implemented in Go.

Implementation of Apriori and Eclat Algorithms (With CPU & GPU)

Apriori Algorithm implementation in TypeScript / JavaScript.

A library of scalable frequent itemset mining algorithms based on Spark

Market Basket Analysis using Apriori Algorithm on grocery data.

MS-Apriori is used for frequent item set mining and association rule learning over transactional data.

This is an implementation of Apriori algorithm for frequent itemset generation and association rule generation. The GUI is made using JAVA FX or Cmd_Line version can be used

Data Mining course projects

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

Data Mining course projects

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

A python code, implementing the Data Mining algorithm - Apriori.

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

Mining recipe data from Allrecipes using collaborative filtering and frequent itemset mining.

Association rule generation using FP Growth algorithm

Data Mining Course Repository, 7th Semester 2023-24, IITD

PCY Algorithm for Frequent Pattern Mining using Pyspark

This repository contains coursework for the Market and Economic Research and Analysis course in the MS Applied Business Analytics program at Boston University.

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

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

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

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