ML Helper
ML Helper is a lightweight Dart library for machine learning. It provides tools for linear regression, metrics, and data preprocessing, fully offline and Flutter-friendly.
Features
- π Linear Regression: A simple and easy-to-use implementation of the linear regression algorithm.
- π§Ό Preprocessing: Essential tools for preparing your data, including
normalizationandtrain/test split. - π Metrics: Evaluate your model's performance with key metrics like
accuracy,recall,f1-score, andMean Squared Error (MSE). - π’ Math Utilities: A collection of helpful math functions such as
mean,standard deviation,sigmoid, andsoftmax. - β‘ Lightweight: Built with zero dependencies to keep your project lean.
- π± Offline & Flutter-Friendly: Works seamlessly in your Dart and Flutter projects without needing an internet connection.
Getting Started
1. Installation
Add this to your package's pubspec.yaml file:
dependencies:
ml_helper: ^0.0.1
Then, run flutter pub get in your terminal.
Usage
Import the package in the file where you want to use it:
import 'package:ml_helper/ml_helper.dart';
Hereβs a quick example of how to use the LinearRegression model:
Code
void main() {
// 1. Sample data
final X = [[1.0], [2.0], [3.0], [4.0]];
final y = [2.0, 4.0, 6.0, 8.0];
// 2. Create and train the model
final model = LinearRegression();
model.fit(X, y);
// 3. Make predictions
final predictions = model.predict([[5.0], [6.0]]);
// The model learned y = 2x, so it should predict [10.0, 12.0]
print('Predictions: $predictions');
}
Additional Information
Feel free to file issues or suggest features on the GitHub repository's Issues tab, For any other inquiries, you can reach me at lutherbanze@gmail.com