Perceptron Neural Network Implementation

This project is a neural network implementation using the perceptron algorithm. It includes a GUI built with Tkinter for parameter input and visualization of training and testing results. The project allows users to train the perceptron model on different datasets and evaluate its performance.

Features

• Interactive GUI:
  • Input parameters such as Epoch and Learning Rate.
  • Select the dataset file through a file picker.
  • Visualize the training and testing results in real-time.
• Training and Testing Workflow:
  • Automatically splits the dataset into training (2/3) and testing (1/3) subsets.
  • Visualizes the classification boundary and outputs:
    • Training Accuracy
    • Testing Accuracy
• Supports Multiple Datasets: The project supports various datasets for evaluating the model.

Datasets

1. perceptron1.txt
2. perceptron2.txt
3. 2Ccircle1.txt
4. 2Circle1.txt
5. 2CloseS.txt
6. 2CloseS2.txt
7. 2CloseS3.txt
8. 2cring.txt
9. 2CS.txt
10. 2Hcircle1.txt
11. 2ring.txt

How to Run

Run the Python code at newperceptron.py.