Enum linfa_clustering::KMeansError

pub enum KMeansError {
    InvalidParams(KMeansParamsError),
    InertiaError,
    LinfaError(Error),
}

An error when modeling a KMeans algorithm

Variants

InvalidParams(KMeansParamsError)

When any of the hyperparameters are set the wrong value

InertiaError

When inertia computation fails

LinfaError(Error)

Trait Implementations

impl Debug for KMeansError

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

Formats the value using the given formatter.

impl Display for KMeansError

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

Formats the value using the given formatter.

impl Error for KMeansError

fn source(&self) -> Option<&(dyn Error + 'static)>

The lower-level source of this error, if any.

fn description(&self) -> &str

👎Deprecated since 1.42.0: use the Display impl or to_string()

fn cause(&self) -> Option<&dyn Error>

👎Deprecated since 1.33.0: replaced by Error::source, which can support downcasting

fn provide<'a>(&'a self, request: &mut Request<'a>)

🔬This is a nightly-only experimental API. (error_generic_member_access)

Provides type based access to context intended for error reports.

impl<F: Float, R: Rng + Clone, DA: Data<Elem = F>, T, D: Distance<F>> Fit<ArrayBase<DA, Dim<[usize; 2]>>, T, KMeansError> for KMeansValidParams<F, R, D>

fn fit( &self, dataset: &DatasetBase<ArrayBase<DA, Ix2>, T> ) -> Result<Self::Object, KMeansError>

Given an input matrix observations, with shape (n_observations, n_features), fit identifies n_clusters centroids based on the training data distribution.

An instance of KMeans is returned.

type Object = KMeans<F, D>

impl From<Error> for KMeansError

fn from(source: Error) -> Self

Converts to this type from the input type.

impl From<KMeansError> for GmmError

fn from(source: KMeansError) -> Self

Converts to this type from the input type.

impl From<KMeansParamsError> for KMeansError

fn from(source: KMeansParamsError) -> Self

Converts to this type from the input type.