Enum linfa_bayes::NaiveBayesError
source · [−]pub enum NaiveBayesError {
Stats(MinMaxError),
InvalidSmoothing(f64),
BaseCrate(Error),
}
Expand description
Error variants from hyper-parameter construction or model estimation
Variants
Stats(MinMaxError)
Error when performing Max operation on data
InvalidSmoothing(f64)
Invalid smoothing parameter
BaseCrate(Error)
Trait Implementations
sourceimpl Debug for NaiveBayesError
impl Debug for NaiveBayesError
sourceimpl Display for NaiveBayesError
impl Display for NaiveBayesError
sourceimpl Error for NaiveBayesError
impl Error for NaiveBayesError
sourcefn source(&self) -> Option<&(dyn Error + 'static)>
fn source(&self) -> Option<&(dyn Error + 'static)>
The lower-level source of this error, if any. Read more
sourcefn backtrace(&self) -> Option<&Backtrace>
fn backtrace(&self) -> Option<&Backtrace>
🔬 This is a nightly-only experimental API. (
backtrace
)Returns a stack backtrace, if available, of where this error occurred. Read more
1.0.0 · sourcefn description(&self) -> &str
fn description(&self) -> &str
👎 Deprecated since 1.42.0:
use the Display impl or to_string()
sourceimpl<F, L, D, T> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, NaiveBayesError> for GaussianNbValidParams<F, L> where
F: Float,
L: Label + Ord,
D: Data<Elem = F>,
T: AsTargets<Elem = L> + Labels<Elem = L>,
impl<F, L, D, T> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, NaiveBayesError> for GaussianNbValidParams<F, L> where
F: Float,
L: Label + Ord,
D: Data<Elem = F>,
T: AsTargets<Elem = L> + Labels<Elem = L>,
type Object = GaussianNb<F, L>
fn fit(
&self,
dataset: &DatasetBase<ArrayBase<D, Ix2>, T>
) -> Result<Self::Object>
sourceimpl<'a, F, L, D, T> FitWith<'a, ArrayBase<D, Dim<[usize; 2]>>, T, NaiveBayesError> for GaussianNbValidParams<F, L> where
F: Float,
L: Label + 'a,
D: Data<Elem = F>,
T: AsTargets<Elem = L> + Labels<Elem = L>,
impl<'a, F, L, D, T> FitWith<'a, ArrayBase<D, Dim<[usize; 2]>>, T, NaiveBayesError> for GaussianNbValidParams<F, L> where
F: Float,
L: Label + 'a,
D: Data<Elem = F>,
T: AsTargets<Elem = L> + Labels<Elem = L>,
type ObjectIn = Option<GaussianNb<F, L>>
type ObjectOut = Option<GaussianNb<F, L>>
fn fit_with(
&self,
model_in: Self::ObjectIn,
dataset: &DatasetBase<ArrayBase<D, Ix2>, T>
) -> Result<Self::ObjectOut>
sourceimpl From<Error> for NaiveBayesError
impl From<Error> for NaiveBayesError
sourceimpl From<MinMaxError> for NaiveBayesError
impl From<MinMaxError> for NaiveBayesError
sourcefn from(source: MinMaxError) -> Self
fn from(source: MinMaxError) -> Self
Performs the conversion.
Auto Trait Implementations
impl RefUnwindSafe for NaiveBayesError
impl Send for NaiveBayesError
impl Sync for NaiveBayesError
impl Unpin for NaiveBayesError
impl UnwindSafe for NaiveBayesError
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcepub fn borrow_mut(&mut self) -> &mut T
pub fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more