Skip to content

Latest commit

 

History

History
65 lines (39 loc) · 1.74 KB

README.md

File metadata and controls

65 lines (39 loc) · 1.74 KB
Raw

Perceptron Implementation in C++

This C++ program demonstrates a basic implementation of a perceptron trained using the loss function and the perceptron trick. The perceptron is a fundamental building block of neural networks and is capable of binary classification.

Getting Started

Prerequisites

  • C++ Compiler

Usage

  1. Clone the repository:

    git clone https://github.com/your-username/perceptron-cpp.git

  2. Compile the C++ program:

    g++ perceptron.cpp -o perceptron

  3. Run the executable:

    ./perceptron

Input Data

The program expects two CSV files:

  1. train.csv - Training data containing input features and corresponding binary labels.
  2. test.csv - Testing data for evaluating the trained perceptron.

Code Overview

  • split_nums: Function to split a string into a vector of doubles.
  • printCols: Function to print input features and labels.
  • sum: Function to calculate the sum of two vectors, including a bias term.
  • classifier: Function to classify input using the trained perceptron.

The program performs training using the perceptron trick and then tests the perceptron on a separate dataset.

Parameters

  • Learning Rate: 0.1
  • Epochs: 1000

Considerations

  • This is a very basic single neuron perceptron with random weights. The sample data given is also very small (~100 rows). So the current outputs may vary a lot. Thus, it is for learning purposes only.

Contributing

Feel free to contribute by opening issues or submitting pull requests.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Acknowledgments

  • Inspired by the concept of perceptrons and neural networks.