fp-tree-implementation

This project is aimed at discovering association rules present in large datasets by using an FP Growth algorithm to extract frequent itemsets. The dataset is a collection of data about female patients at least 21 years old of Pima Indian heritage. There are 9 attributes and the algorithm is applied to generate frequent itemsets and their corresponding associative rules.

Code:

DM2.cpp

Input file:

input.txt

Link for actual dataset:

https://archive.ics.uci.edu/ml/datasets/Pima+Indians+Diabetes