sklearn-rs

A scikit-learn inspired machine learning library in Rust.

Features

• Linear Regression
• Evaluation Metrics (MSE, MAE, R²)
• Type-safe API
• Comprehensive error handling

Quick Start

[dependencies]

sklearn-rs = "0.1.0"



use sklearn_rs::{LinearRegression, Estimator, Predictor};

use ndarray::array;



fn main() -> Result<(), Box<dyn std::error::Error>> {

    let x = array![[1.0], [2.0], [3.0]];

    let y = array![2.0, 4.0, 6.0];

    

    let model = LinearRegression::default().fit(&x, &y)?;

    let predictions = model.predict(&x)?;

    

    println!("Predictions: {:?}", predictions);

    Ok(())

}

License

MIT





# sklearn-rs



[![Crates.io](https://img.shields.io/crates/v/sklearn-rs.svg)](https://crates.io/crates/sklearn-rs)

[![Documentation](https://docs.rs/sklearn-rs/badge.svg)](https://docs.rs/sklearn-rs)

[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)



一个受 scikit-learn 启发的 Rust 机器学习库。



## 功能特性



- 🚀 **线性回归** - 完整的线性回归实现

- 📊 **评估指标** - MSE, MAE, R² 分数

- 🔒 **类型安全** - Rust 强类型系统保障

- 🛡️ **错误处理** - 完善的验证和错误信息

- 📚 **中文文档** - 完整的中文文档支持



## 安装



在 `Cargo.toml` 中添加：



```toml

[dependencies]

sklearn-rs = "0.1.0"

ndarray = "0.15"