Struct rusty_machine::learning::k_means::KMeansClassifier [−] [src]

pub struct KMeansClassifier {
    pub iters: usize,
    pub k: usize,
    pub centroids: Option<Matrix<f64>>,
    pub init_algorithm: InitAlgorithm,
}

K-Means Classification model.

Contains option for centroids. Specifies iterations and number of classes.

Fields

iters: usize

Max iterations of algorithm to run.

k: usize

The number of classes.

centroids: Option<Matrix<f64>>

The fitted centroids .

init_algorithm: InitAlgorithm

The initial algorithm to use.

Methods

impl KMeansClassifier
[src]

fn new(k: usize) -> KMeansClassifier

Constructs untrained k-means classifier model.

Requires number of classes to be specified. Defaults to 100 iterations and kmeans++ initialization.

Examples

use rusty_machine::learning::k_means::KMeansClassifier;

let model = KMeansClassifier::new(5);

Trait Implementations

impl UnSupModel<Matrix<f64>, Vector<usize>> for KMeansClassifier
[src]

fn predict(&self, inputs: &Matrix<f64>) -> Vector<usize>

Predict classes from data.

Model must be trained.

fn train(&mut self, inputs: &Matrix<f64>)

Train the classifier using input data.