Naive Bayes
linfa-bayes
provides pure Rust implementations of Naive Bayes algorithms for the Linfa toolkit.
The Big Picture
linfa-bayes
is a crate in the linfa
ecosystem, an effort to create a toolkit for classical Machine Learning implemented in pure Rust, akin to Python's scikit-learn
.
Current state
linfa-bayes
currently provides an implementation of the following methods:
- Gaussian Naive Bayes (GaussianNB)
Examples
You can find an example in the examples/
directory. To run, use:
use ToConfusionMatrix;
use ;
use ;
// Read in the dataset and convert targets to binary data
let = winequality
.map_targets
.split_with_ratio;
// Train the model
let model = params.fit?;
// Predict the validation dataset
let pred = model.predict;
// Construct confusion matrix
let cm = pred.confusion_matrix?;
// classes | bad | good
// bad | 130 | 12
// good | 7 | 10
//
// accuracy 0.8805031, MCC 0.45080978
println!;
println!;
# Result Ok