Struct OutlierDetector 

pub struct OutlierDetector<State = Untrained> { /* private fields */ }

Univariate outlier detector for identifying anomalous data points

This detector provides several methods for identifying outliers in univariate data:

• Z-score: Points with |z-score| > threshold are considered outliers
• Modified Z-score: Uses median and MAD instead of mean and std for robustness
• IQR: Points outside Q1 - kIQR or Q3 + kIQR are considered outliers
• Percentile: Points outside specified percentile bounds are considered outliers

Implementations

impl OutlierDetector<Untrained>

pub fn new() -> Self

Create a new OutlierDetector

pub fn z_score(threshold: Float) -> Self

Create Z-score based outlier detector

pub fn iqr(multiplier: Float) -> Self

Create IQR-based outlier detector

pub fn mahalanobis_distance(confidence_level: Float) -> Self

Create Mahalanobis distance based outlier detector

pub fn method(self, method: OutlierDetectionMethod) -> Self

Set the detection method

pub fn threshold(self, threshold: Float) -> Self

Set the threshold

impl OutlierDetector<Trained>

pub fn statistics(&self) -> &OutlierStatistics

Get fitted statistics

pub fn n_features_in(&self) -> usize

Get number of input features

pub fn is_outlier_single(&self, feature_idx: usize, value: Float) -> bool

Check if a single feature value is an outlier

pub fn detect_outliers( &self, x: &Array2<Float>, ) -> Result<OutlierDetectionResult>

Generate detailed outlier detection results

pub fn outlier_scores(&self, x: &Array2<Float>) -> Result<Vec<Float>>

Compute outlier scores

Trait Implementations

impl<State: Clone> Clone for OutlierDetector<State>

fn clone(&self) -> OutlierDetector<State>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<State: Debug> Debug for OutlierDetector<State>

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

Formats the value using the given formatter.

impl Default for OutlierDetector<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ()> for OutlierDetector<Untrained>

type Fitted = OutlierDetector<Trained>

The fitted model type

fn fit(self, x: &Array2<Float>, _y: &()) -> Result<Self::Fitted>

Fit the model to the provided data with validation

fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>

where Self: Sized,

Fit with custom validation and early stopping

impl Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<bool>, Dim<[usize; 2]>>> for OutlierDetector<Trained>

fn transform(&self, x: &Array2<Float>) -> Result<Array2<bool>>

Transform the input data