Enum linfa_clustering::KMeansError

pub enum KMeansError {
    InvalidValue(String),
    InertiaError(String),
    NotConverged(String),
    LinfaError(Error),
}

An error when modeling a KMeans algorithm

Variants

InvalidValue(String)

When any of the hyperparameters are set the wrong value

InertiaError(String)

When inertia computation fails

NotConverged(String)

When fitting algorithm does not converge

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.

pub fn backtrace(&self) -> Option<&Backtrace>

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

Returns a stack backtrace, if available, of where this error occurred.

pub fn description(&self) -> &str

👎 Deprecated since 1.42.0:

use the Display impl or to_string()

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

👎 Deprecated since 1.33.0:

replaced by Error::source, which can support downcasting

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

type Object = KMeans<F>

fn fit(
    &self,
    dataset: &DatasetBase<ArrayBase<D, 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.

impl From<Error> for KMeansError

fn from(source: Error) -> Self

Performs the conversion.

impl From<KMeansError> for GmmError

fn from(source: KMeansError) -> Self

Performs the conversion.