Struct petal_clustering::HDbscan

pub struct HDbscan<A, M> {
    pub eps: A,
    pub alpha: A,
    pub min_samples: usize,
    pub min_cluster_size: usize,
    pub metric: M,
    pub boruvka: bool,
}

Fields

eps: A

The radius of a neighborhood.

alpha: A

min_samples: usize

The minimum number of points required to form a dense region.

min_cluster_size: usize

metric: M

boruvka: bool

Trait Implementations

impl<A: Debug, M: Debug> Debug for HDbscan<A, M>

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

Formats the value using the given formatter.

impl<A> Default for HDbscan<A, Euclidean> where
    A: Float, 

fn default() -> Self

Returns the “default value” for a type.

impl<'de, A, M> Deserialize<'de> for HDbscan<A, M> where
    A: Deserialize<'de>,
    M: Deserialize<'de>, 

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<S, A, M> Fit<ArrayBase<S, Dim<[usize; 2]>>, (HashMap<usize, Vec<usize, Global>, RandomState>, Vec<usize, Global>)> for HDbscan<A, M> where
    A: AddAssign + DivAssign + Float + FromPrimitive + Sync + Send + TryFrom<u32>,
    <A as TryFrom<u32>>::Error: Debug,
    S: Data<Elem = A>,
    M: Metric<A> + Clone + Sync + Send, 

fn fit(
    &mut self,
    input: &ArrayBase<S, Ix2>
) -> (HashMap<usize, Vec<usize>>, Vec<usize>)

impl<A, M> Serialize for HDbscan<A, M> where
    A: Serialize,
    M: Serialize, 

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.