sklears (crate)

Latest release: 0.1.0-beta.1 (January 1, 2026). See the workspace release notes for highlights and upgrade guidance.

Overview

This crate exposes the top-level sklears API that bundles all subcrates into a cohesive, scikit-learn compatible experience. It provides re-exports, prelude shortcuts, and integrated feature flag management.

Key Features

• Unified Prelude: Access estimators, transformers, pipelines, and utilities through a single import.
• Feature Flags: Enable only the modules you need (linear, ensemble, gpu, etc.) to keep builds lightweight.
• Rust + Python: Designed to work with both native Rust projects and the sklears-python bindings.
• Documentation Hub: Acts as the canonical entry point for examples, tutorials, and integration guides.

Quick Start

[dependencies]
sklears = { version = "0.1.0-beta.1", features = ["linear", "ensemble", "gpu"] }

use sklears::prelude::*;
use scirs2_core::ndarray::{array, Array1};

let x = array![
    [0.0, 1.0],
    [1.0, 0.0],
    [1.0, 1.0],
];
let y = Array1::from(vec![0, 1, 1]);

let model = RandomForestClassifier::new()
    .n_estimators(200)
    .fit(&x, &y)?;

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

Status

• Serves as the umbrella crate validated through the 11,292 passing workspace tests for 0.1.0-beta.1.
• Re-export map kept in sync with individual module READMEs and documentation.
• Further enhancements (module-level doc consolidation, feature flag audits) tracked in TODO.md.