FP-Growth Algorithm with Python and Tkinter

The FP-Growth Algorithm with Python and Tkinter is a graphical user interface (GUI) application that simplifies the process of discovering frequent patterns in transactional datasets. Built using the pyfpgrowth library, it leverages the FP-Growth algorithm—an efficient and scalable approach to frequent pattern mining that avoids generating candidate sets. The application provides a user-friendly interface powered by tkinter, allowing users to input transactions, specify a minimum support threshold, and instantly view the results in a clear, organized format. This tool is ideal for those who need a simple yet powerful way to analyze transactional data without delving into complex coding or command-line operations.

Features

• Input transactional data in a text field (comma-separated items per transaction).
• Set a custom minimum support threshold.
• Identify frequent item patterns using the FP-Growth algorithm.
• Results are displayed in a scrollable output window.

Installation

1. Clone the repository:

   git clone https://Trickybutshruti/FP-growth-Algorithm
   cd FP-growth-Algorithm

2. Install dependencies:

   Ensure you have Python installed. Then, install the required libraries:

   pip install pyfpgrowth

3. Run the application:

   python fp_growth_tkinter.py

Usage

1. Open the application.
2. Input transactions in the text area. Each line should represent a transaction, with items separated by commas (e.g., milk,bread,eggs).
3. Enter a minimum support value (e.g., 0.5 for 50%).
4. Click the Run FP-Growth button to find frequent patterns.
5. View the results in the output window.

Requirements

• Python 3.x
• Libraries: tkinter (built-in), pyfpgrowth

Project Structure

• fp_growth_tkinter.py: The main script containing the application code.