Struct DBSCAN 

pub struct DBSCAN { /* private fields */ }

DBSCAN clustering algorithm

Implementations

impl DBSCAN

pub fn new(eps: f64, min_samples: usize) -> Self

Create new DBSCAN

pub fn eps(self, eps: f64) -> Self

Set eps

pub fn min_samples(self, min_samples: usize) -> Self

Set min_samples

pub fn labels(&self) -> Option<&Array1<i32>>

Get labels

pub fn core_sample_indices(&self) -> &[usize]

Get core sample indices

pub fn n_clusters(&self) -> Option<usize>

Get number of clusters found

Trait Implementations

impl SklearnClusterer for DBSCAN

fn predict(&self, _X: &Array2<f64>) -> Result<Array1<i32>>

Predict cluster labels

fn fit_predict(&mut self, X: &Array2<f64>) -> Result<Array1<i32>>

Fit and predict in one step

fn cluster_centers(&self) -> Option<&Array2<f64>>

Get cluster centers (if applicable)

impl SklearnEstimator for DBSCAN

fn fit(&mut self, X: &Array2<f64>, _y: Option<&Array1<f64>>) -> Result<()>

Fit the model to training data

fn get_params(&self) -> HashMap<String, String>

Get model parameters

fn set_params(&mut self, params: HashMap<String, String>) -> Result<()>

Set model parameters

fn is_fitted(&self) -> bool

Check if model is fitted

fn get_feature_names_out(&self) -> Vec<String>

Get feature names