Enum ElasticNetError

pub enum ElasticNetError {
    NotEnoughSamples,
    IllConditioned,
    InvalidL1Ratio(f32),
    InvalidPenalty(f32),
    InvalidTolerance(f32),
    IncorrectTargetShape,
    BaseCrate(Error),
}

Error variants from hyperparameter construction or model estimation

Variants

NotEnoughSamples

The input has not enough samples

IllConditioned

The input is singular

InvalidL1Ratio(f32)

InvalidPenalty(f32)

InvalidTolerance(f32)

IncorrectTargetShape

BaseCrate(Error)

Trait Implementations

impl Clone for ElasticNetError

fn clone(&self) -> ElasticNetError

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ElasticNetError

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

Formats the value using the given formatter.

impl Display for ElasticNetError

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

Formats the value using the given formatter.

impl Error for ElasticNetError

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

Returns 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, D, T> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, ElasticNetError> for ElasticNetValidParams<F>

where F: Float, D: Data<Elem = F>, T: AsSingleTargets<Elem = F>,

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

Fit an elastic net model given a feature matrix x and a target variable y.

The feature matrix x must have shape (n_samples, n_features)

The target variable y must have shape (n_samples)

Returns a FittedElasticNet object which contains the fitted parameters and can be used to predict values of the target variable for new feature values.

type Object = ElasticNet<F>

impl<F, D, T> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, ElasticNetError> for MultiTaskElasticNetValidParams<F>

where F: Float, T: AsMultiTargets<Elem = F>, D: Data<Elem = F>,

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

Fit a multi-task Elastic Net model given a feature matrix x and a target matrix y.

The feature matrix x must have shape (n_samples, n_features)

The target variable y must have shape (n_samples, n_tasks)

Returns a FittedMultiTaskElasticNet object which contains the fitted parameters and can be used to predict values of the target variables for new feature values.

type Object = MultiTaskElasticNet<F>

impl From<Error> for ElasticNetError

fn from(source: Error) -> Self

Converts to this type from the input type.