Enum linfa_elasticnet::ElasticNetError

pub enum ElasticNetError {
    NotEnoughSamples,
    IllConditioned,
    InvalidL1Ratio(f32),
    InvalidPenalty(f32),
    InvalidTolerance(f32),
    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)

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)>

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, 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 From<Error> for ElasticNetError

fn from(source: Error) -> Self

Converts to this type from the input type.