Crate aprender 

Aprender: Next-generation machine learning library in pure Rust.

Aprender provides production-grade ML algorithms with a focus on ergonomic APIs, comprehensive testing, and backend-agnostic compute.

Quick Start

use aprender::prelude::*;

// Create training data (y = 2*x + 1)
let x = Matrix::from_vec(4, 1, vec![
    1.0,
    2.0,
    3.0,
    4.0,
]).unwrap();
let y = Vector::from_slice(&[3.0, 5.0, 7.0, 9.0]);

// Train linear regression
let mut model = LinearRegression::new();
model.fit(&x, &y).unwrap();

// Make predictions
let predictions = model.predict(&x);
let r2 = model.score(&x, &y);
assert!(r2 > 0.99);

Modules

• primitives: Core Vector and Matrix types
• data: DataFrame for named columns
• linear_model: Linear regression algorithms
• cluster: Clustering algorithms (K-Means)
• tree: Decision tree classifiers
• metrics: Evaluation metrics
• model_selection: Cross-validation and train/test splitting

Re-exports

pub use primitives::Matrix;

pub use primitives::Vector;

pub use traits::Estimator;

pub use traits::Transformer;

pub use traits::UnsupervisedEstimator;

Modules

cluster

Clustering algorithms.

data

DataFrame module for named column containers.

linear_model

Linear models for regression.

metrics

Evaluation metrics for ML models.

model_selection

Model selection utilities for cross-validation and train/test splitting.

prelude

Convenience re-exports for common usage.

primitives

Core compute primitives (Vector, Matrix).

traits

Core traits for ML estimators and transformers.

tree

Decision tree algorithms for classification.