Crate rusty_science

rusty_science

An easy to learn and use ML toolkit for rust

Installation

[dependencies]
rusty_science = "0.1.1"

Usage Example

use rusty_science::classification::knn::KNNClassifier;
let mut knn = KNNClassifier::new(3);
let data = vec![vec![1.0, 2.0], vec![2.0, 3.0], vec![3.0, 4.0]];
let labels = vec![0, 1, 0];
knn.fit(data, labels);
let prediction = knn.predict(vec![2.5, 3.5]);
println!("Predicted label: {}", prediction);

Modules

• classification: A set of classification models
• clustering: A set of clustering models
• data: A set of tools for the manipulation or importing of data
• linear_models: A set of linear models
• metrics: Tools to test the output of models
• regression: A set of regression models

License

Licensed under MIT.

Contribution

Contributions are welcome! Please feel free to submit a pull request or file an issue.

Acknowledgements

If applicable, acknowledge other libraries or individuals that helped in developing this crate.

Contributors

Cooper Brown, Jack Welsh

Modules

classification

clustering

Clustering Algorithms

data

linear_models

metrics

regression

Macros

panic_dimension_mismatch

panic_labels_not_binary

panic_matrix_inversion

panic_missing_coefficients

panic_untrained