Struct rusty_machine::learning::knn::KNNClassifier

pub struct KNNClassifier<S: KNearestSearch> { /* private fields */ }

k-Nearest Neighbor Classifier

Implementations

impl KNNClassifier<KDTree>

pub fn new(k: usize) -> Self

Constructs an untrained KNN Classifier with specified number of search neighbors.

Examples

use rusty_machine::learning::knn::KNNClassifier;
let _ = KNNClassifier::new(3);

impl<S: KNearestSearch> KNNClassifier<S>

pub fn new_specified(k: usize, searcher: S) -> Self

Constructs an untrained KNN Classifier with specified k and leafsize for KDTree.

Examples

use rusty_machine::learning::knn::{KNNClassifier, BallTree};
let _ = KNNClassifier::new_specified(3, BallTree::new(10));

Trait Implementations

impl<S: Debug + KNearestSearch> Debug for KNNClassifier<S>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for KNNClassifier<KDTree>

fn default() -> Self

Constructs an untrained KNN Classifier with searching 5 neighbors.

Examples

use rusty_machine::learning::knn::KNNClassifier;
let _ = KNNClassifier::default();

impl<S: KNearestSearch> SupModel<Matrix<f64>, Vector<usize>> for KNNClassifier<S>

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

Predict output from inputs.

fn train(
    &mut self,
    inputs: &Matrix<f64>,
    targets: &Vector<usize>
) -> LearningResult<()>

Train the model using inputs and targets.