🧩 Apriori Algorithm Visualizer

Hello! This is an algorithm I learned in my first semester while doing the MCS program at UIUC. It is an interactive web-based visualizer for the Apriori algorithm, built using Flask, Plotly, and Pandas.
Upload your own transaction dataset and explore how frequent itemsets and association rules are generated in real-time.

🧠 What It Does

The app applies the Apriori algorithm to discover associations between items in large transactional datasets.
For example, it can automatically discover patterns like:

🥛 Milk + 🍞 Bread → 🧈 Butter (Support: 0.25, Confidence: 0.8, Lift: 1.5)

⚙️ Setup & Installation

1️⃣ Clone the Repository

git clone https://github.com/YOUR_USERNAME/apriori-visualizer.git
cd apriori-visualizer

2️⃣ Create a Virtual Environment (Recommended)

python3 -m venv venv
source venv/bin/activate  # macOS/Linux
# or
venv\Scripts\activate     # Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Run the App

python app.py

Then open in your browser:
👉 http://127.0.0.1:5000

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📊 Example CSV Format

Upload a CSV like this (1 = item bought, 0 = not bought):

milk	bread	butter	eggs	apples
1	1	0	0	0
1	1	1	0	0
0	1	1	1	1
1	0	0	0	1

Or generate your own large dataset:

python generate_dataset.py