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40 lines
1.0 KiB
Markdown
40 lines
1.0 KiB
Markdown
# Machine Learning
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RustFrame ships with several algorithms:
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- Linear and logistic regression
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- K-means clustering
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- Principal component analysis (PCA)
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- Naive Bayes and dense neural networks
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## Linear Regression
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```rust
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# extern crate rustframe;
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use rustframe::compute::models::linreg::LinReg;
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use rustframe::matrix::Matrix;
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let x = Matrix::from_vec(vec![1.0, 2.0, 3.0, 4.0], 4, 1);
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let y = Matrix::from_vec(vec![2.0, 3.0, 4.0, 5.0], 4, 1);
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let mut model = LinReg::new(1);
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model.fit(&x, &y, 0.01, 100);
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let preds = model.predict(&x);
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assert_eq!(preds.rows(), 4);
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```
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## K-means Walkthrough
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```rust
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# extern crate rustframe;
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use rustframe::compute::models::k_means::KMeans;
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use rustframe::matrix::Matrix;
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let data = Matrix::from_vec(vec![1.0, 1.0, 5.0, 5.0], 2, 2);
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let (model, _labels) = KMeans::fit(&data, 2, 10, 1e-4);
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let new_point = Matrix::from_vec(vec![0.0, 0.0], 1, 2);
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let cluster = model.predict(&new_point)[0];
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```
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For helper functions and upcoming modules, visit the
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[utilities](./utilities.md) section.
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