Struct linfa_clustering::DbscanValidParams

pub struct DbscanValidParams<F: Float, D: Distance<F>, N: NearestNeighbour> { /* fields omitted */ }

The set of hyperparameters that can be specified for the execution of the DBSCAN algorithm.

Implementations

impl<F: Float, D: Distance<F>, N: NearestNeighbour> DbscanValidParams<F, D, N>

pub fn tolerance(&self) -> F

Nearest neighbour algorithm used for range queries

pub fn minimum_points(&self) -> usize

Minimum number of neighboring points a point needs to have to be a core
point and not a noise point.

pub fn dist_fn(&self) -> &D

Distance metric used in the DBSCAN calculation

pub fn nn_algo(&self) -> &N

Nearest neighbour algorithm used for range queries

Trait Implementations

impl<F: Debug + Float, D: Debug + Distance<F>, N: Debug + NearestNeighbour> Debug for DbscanValidParams<F, D, N>

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

Formats the value using the given formatter.

impl<F: Float, D: Data<Elem = F>, DF: Distance<F>, N: NearestNeighbour> Transformer<&'_ ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<Option<usize>>, Dim<[usize; 1]>>> for DbscanValidParams<F, DF, N>

fn transform(&self, observations: &ArrayBase<D, Ix2>) -> Array1<Option<usize>>

impl<F: Float, D: Data<Elem = F>, DF: Distance<F>, N: NearestNeighbour, T> Transformer<DatasetBase<ArrayBase<D, Dim<[usize; 2]>>, T>, DatasetBase<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<Option<usize>>, Dim<[usize; 1]>>>> for DbscanValidParams<F, DF, N>

fn transform(
    &self,
    dataset: DatasetBase<ArrayBase<D, Ix2>, T>
) -> DatasetBase<ArrayBase<D, Ix2>, Array1<Option<usize>>>