Enum linfa_preprocessing::error::PreprocessingError

#[non_exhaustive]
pub enum PreprocessingError {
    WrongMeasureForScaler(String, String),
    TooManySubsamples(usize, usize),
    NotEnoughSamples,
    InvalidFloat,
    FlippedMinMaxRange,
    InvalidNGramBoundaries(usize, usize),
    FlippedNGramBoundaries(usize, usize),
    InvalidDocumentFrequencies(f32, f32),
    FlippedDocumentFrequencies(f32, f32),
    RegexError(Error),
    IoError(Error),
    EncodingError(Cow<'static, str>),
    LinalgError(LinalgError),
    NdarrayStatsEmptyError(EmptyInput),
    LinfaError(Error),
}

Variants (Non-exhaustive)

Non-exhaustive enums could have additional variants added in future. Therefore, when matching against variants of non-exhaustive enums, an extra wildcard arm must be added to account for any future variants.

WrongMeasureForScaler(String, String)

TooManySubsamples(usize, usize)

NotEnoughSamples

InvalidFloat

FlippedMinMaxRange

InvalidNGramBoundaries(usize, usize)

FlippedNGramBoundaries(usize, usize)

InvalidDocumentFrequencies(f32, f32)

FlippedDocumentFrequencies(f32, f32)

RegexError(Error)

IoError(Error)

EncodingError(Cow<'static, str>)

LinalgError(LinalgError)

NdarrayStatsEmptyError(EmptyInput)

LinfaError(Error)

Trait Implementations

impl Debug for PreprocessingError

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

Formats the value using the given formatter.

impl Display for PreprocessingError

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

Formats the value using the given formatter.

impl Error for PreprocessingError

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

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: Float, D: Data<Elem = F>, T: AsTargets> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, PreprocessingError> for LinearScalerParams<F>

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

Fits the input dataset accordng to the scaler method. Will return an error if the dataset does not contain any samples or (in the case of MinMax scaling) if the specified range is not valid.

type Object = LinearScaler<F>

impl<F: Float, D: Data<Elem = F>, T: AsTargets> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, PreprocessingError> for Whitener

type Object = FittedWhitener<F>

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

impl From<EmptyInput> for PreprocessingError

fn from(source: EmptyInput) -> Self

Converts to this type from the input type.

impl From<Error> for PreprocessingError

fn from(source: Error) -> Self

Converts to this type from the input type.

impl From<Error> for PreprocessingError

fn from(source: Error) -> Self

Converts to this type from the input type.

impl From<Error> for PreprocessingError

fn from(source: Error) -> Self

Converts to this type from the input type.

impl From<LinalgError> for PreprocessingError

fn from(source: LinalgError) -> Self

Converts to this type from the input type.