Struct DBSCAN 

pub struct DBSCAN { /* private fields */ }

DBSCAN Model

Implements clustering using the DBSCAN algorithm via the UnSupModel trait.

Implementations

impl DBSCAN

pub fn new(eps: f64, min_points: usize) -> DBSCAN

Create a new DBSCAN model with a given distance episilon and minimum points per cluster.

pub fn set_predictive(&mut self, predictive: bool)

Set predictive to true if the model is to be used to classify future points.

If the model is set as predictive then the input data will be cloned during training.

pub fn clusters(&self) -> Option<&Vector<Option<usize>>>

Return an Option pointing to the model clusters.

Trait Implementations

impl Debug for DBSCAN

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

Formats the value using the given formatter.

impl Default for DBSCAN

Constructs a non-predictive DBSCAN model with the following parameters:

• eps : 0.5
• min_points : 5

fn default() -> DBSCAN

Returns the “default value” for a type.

impl UnSupModel<Matrix<f64>, Vector<Option<usize>>> for DBSCAN

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

Train the classifier using input data.

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

Predict output from inputs.