Enum linfa_clustering::GmmError

pub enum GmmError {
    InvalidValue(String),
    LinalgError(LinalgError),
    EmptyCluster(String),
    LowerBoundError(String),
    NotConverged(String),
    KMeansError(KMeansError),
    LinfaError(Error),
    MinMaxError(MinMaxError),
}

An error when modeling a GMM algorithm

Variants

InvalidValue(String)

When any of the hyperparameters are set the wrong value

Tuple Fields of InvalidValue

0: String

LinalgError(LinalgError)

Errors encountered during linear algebra operations

Tuple Fields of LinalgError

0: LinalgError

EmptyCluster(String)

When a cluster has no more data point while fitting GMM

Tuple Fields of EmptyCluster

0: String

LowerBoundError(String)

When lower bound computation fails

Tuple Fields of LowerBoundError

0: String

NotConverged(String)

When fitting EM algorithm does not converge

Tuple Fields of NotConverged

0: String

KMeansError(KMeansError)

When initial KMeans fails

Tuple Fields of KMeansError

0: KMeansError

LinfaError(Error)

Tuple Fields of LinfaError

0: Error

MinMaxError(MinMaxError)

Tuple Fields of MinMaxError

0: MinMaxError

Trait Implementations

impl Debug for GmmError

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

Formats the value using the given formatter.

impl Display for GmmError

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

Formats the value using the given formatter.

impl Error for GmmError

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

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

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

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

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

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

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

type Object = GaussianMixtureModel<F>

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

impl From<Error> for GmmError

fn from(source: Error) -> Self

Performs the conversion.

impl From<KMeansError> for GmmError

fn from(source: KMeansError) -> Self

Performs the conversion.

impl From<LinalgError> for GmmError

fn from(source: LinalgError) -> Self

Performs the conversion.

impl From<MinMaxError> for GmmError

fn from(source: MinMaxError) -> Self

Performs the conversion.