Mining Association Rules and Frequent Itemsets with R

Visualizing Association Rules and Frequent Itemsets with R

Classification Based on Association Rules in R

This Repository Contains R-Codes executed on various Datasets in RStudio. I Hope This Repository is very helpful for those who are Willing to build their Career in Data Science, Big Data.

linguistic fuzzy logic algorithms: mining for linguistic fuzzy association rules, composition of fuzzy relations, performing perception-based logical deduction (PbLD), and forecasting time-series using fuzzy rule-based ensemble (FRBE)

The repository contains exercises on Machine Learning algorithms in R, using RStudio. Used to dive into ML, data preprocessing, data visualisation, and data exploration.

Web app for mining and visually analyzing association rules.

Market Basket Analysis with R

Complete package for all Data Science models using R. Starting form Preprocessing, Data Manipulation, Feature Engineering, Model Building, and Model Validation.

Finding Associations Between Location, Crime Type and Crime Outcome in Swindon and Wiltshire

R Files for Phd Research

Classification Based on Association Rules in R

Association Rules for regex patterns in amino acid sequences

Repository for Customer Segment Analysis using Python & Shiny App Dashboard

Use of associative rule mining using the APRIORI algorithm

Repo consists the most of the machine learning algorithms in the R language. I am also demonstrated the Hypothesis Testing in-depth with R solutions.

Extract knowledge from a data using different techniques, including Association Rules Hierarchical Agglomerative Clustering (HAC) K-means Clustering Decision Trees

Market Basket Analysis is one of the key techniques used by large retailers to uncover associations between items. It works by looking for combinations of items that occur together frequently in transactions. To put it another way, it allows retailers to identify relationships between the items that people buy.

Loyola Chicago Course - INFS 348