Enum LearningError 

pub enum LearningError {
    InvalidDimension,
    InsufficientData,
    Singular,
    NotConverged,
}

Errors common to the learning estimators. Estimators fail closed (return an error) rather than emit a fabricated fit — consistent with the engine-wide honesty rule.

Variants

InvalidDimension

Input shapes are inconsistent (lengths / row×col mismatch).

InsufficientData

Not enough data for the requested fit (e.g. fewer samples than parameters).

Singular

The system is singular / rank-deficient (e.g. collinear predictors) — fail closed instead of returning a meaningless solution.

NotConverged

An iterative fit did not converge within its iteration budget.

Trait Implementations

impl Clone for LearningError

fn clone(&self) -> LearningError

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for LearningError

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

Formats the value using the given formatter.

impl Display for LearningError

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

Formats the value using the given formatter.

impl Error for LearningError

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 From<SolversError> for LearningError

fn from(e: SolversError) -> Self

Converts to this type from the input type.

impl PartialEq for LearningError

fn eq(&self, other: &LearningError) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Eq for LearningError

impl StructuralPartialEq for LearningError