# [rs-ml](https://docs.rs/rs-ml/latest/rs_ml)
ML framework for the rust programming language. It includes traits for
transfomers, models, and an implementation for scalers, and a gaussian Naive
Bayesian classifier.
## Usage
This library requires a compute backend to perform matrix operations. Compute
backends are exposed with provided feature flags. Refer to the
[ndarray_linalg](https://github.com/rust-ndarray/ndarray-linalg?tab=readme-ov-file#backend-features)
docs for more information.
## Design
### Classifiers
- iterative
- Can be trained with streaming data that does not fit in memory at the same time
- non-iterative
- Must have the entire dataset at one time to train the model
```rust
let a = csv::read_csv("filename.csv")?;
let features = Dataset::from_struct(a, |r| arr1[r.f1, r.f2, r.f3], |r| r.label)?;
let model = GaussianNB::fit(features)?;
```