Expand description
rs-ml is a simple ML framework for the Rust language. it includes train test splitting, scalers, and a guassian naive bayes model. It also includes traits to add more transfomers and models to the framework.
§Usage
This library requires a compute backend to perform matrix operations. Compute backends are exposed with provided feature flags. Refer to the ndarray_linalg docs for more information.
Modules§
- classification
- Commonly used classification models.
- dimensionality_
reduction - Dimensionality reduction techniques
- metrics
- Commonly used metrics for classification and regression models.
- regression
- Commonly used regression models.
- transformer
- Functionality to transform and scale data.
Structs§
- Split
Dataset - Train test split result. returns in order training features, testing features, training labels, testing labels.
Traits§
- Estimatable
- Trait to prepare a struct for training or inference
- Estimator
- Trait for fitting classification and regression models, and transformers.
Functions§
- train_
test_ split - Split data and features into training and testing set.
test_sizemust be between 0 and 1.