Enum linfa_preprocessing::error::Error

pub enum Error {
    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

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 Error

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

Formats the value using the given formatter.

impl Display for Error

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

Formats the value using the given formatter.

impl Error for Error

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

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

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

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

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

pub fn description(&self) -> &str

👎 Deprecated since 1.42.0:

use the Display impl or to_string()

pub fn cause(&self) -> Option<&dyn Error>

👎 Deprecated since 1.33.0:

replaced by Error::source, which can support downcasting

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

type Object = FittedLinearScaler<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.

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

type Object = FittedWhitener<F>

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

impl From<EmptyInput> for Error

fn from(source: EmptyInput) -> Self

Performs the conversion.

impl From<Error> for Error

fn from(source: Error) -> Self

Performs the conversion.

impl From<Error> for Error

fn from(source: Error) -> Self

Performs the conversion.

impl From<Error> for Error

fn from(source: Error) -> Self

Performs the conversion.

impl From<LinalgError> for Error

fn from(source: LinalgError) -> Self

Performs the conversion.