A simple, generic implementation of a Perceptron in Go (Golang), supporting multi-dimensional datasets and optional training history recording.
Disclaimer
This project was created only for educational purposes.
There are no guarantees regarding correctness, performance, or suitability for any real-world application.
Overview
This package implements a basic linear binary classifier (perceptron) for numeric datasets.
It supports:
Training on multi-dimensional features.
2D Example:
3D Example:
Training history tracking (optional) — including weights, bias, and mean error after each epoch.
Features
Trainable perceptron with a customizable learning rate and epochs.
Predict new data points after training.
Access complete training history for analysis or visualization.
Lightweight and dependency-free (except for golang.org/x/exp/constraints).