Struct LocalOutlierFactor 

pub struct LocalOutlierFactor {
    pub n_neighbors: usize,
    pub contamination: f64,
    pub algorithm: String,
    pub scores: Option<Vec<f64>>,
    pub feature_columns: Option<Vec<String>>,
}

Local Outlier Factor for anomaly detection

Local Outlier Factor computes the local density deviation of a point with respect to its neighbors, identifying points that have significantly lower density than their neighbors.

Fields

n_neighbors: usize

Number of neighbors to consider

contamination: f64

Contamination: expected proportion of outliers in the data

algorithm: String

Algorithm to use for nearest neighbors search

scores: Option<Vec<f64>>

Anomaly scores (-1 for anomalies, 1 for normal points)

feature_columns: Option<Vec<String>>

Feature columns used for anomaly detection

Implementations

impl LocalOutlierFactor

pub fn new(n_neighbors: usize) -> Self

Create a new LocalOutlierFactor instance

pub fn anomaly_scores(&self) -> &[f64]

Get anomaly scores

pub fn labels(&self) -> &[i64]

Get anomaly labels (1 for normal, -1 for anomalies)

pub fn contamination(self, contamination: f64) -> Self

Set contamination (expected proportion of outliers)

pub fn algorithm(self, algorithm: &str) -> Self

Set algorithm for nearest neighbors search

pub fn with_columns(self, columns: Vec<String>) -> Self

Specify feature columns to use

Trait Implementations

impl Clone for LocalOutlierFactor

fn clone(&self) -> LocalOutlierFactor

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for LocalOutlierFactor

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

Formats the value using the given formatter.

impl ModelEvaluator for LocalOutlierFactor

fn evaluate( &self, _test_data: &DataFrame, _test_target: &str, ) -> Result<ModelMetrics>

Evaluate a model using test data

fn cross_validate( &self, _data: &DataFrame, _target: &str, _folds: usize, ) -> Result<Vec<ModelMetrics>>

Cross-validate a model

impl UnsupervisedModel for LocalOutlierFactor

fn fit(&mut self, data: &DataFrame) -> Result<()>

Fit model to training data

fn transform(&self, _data: &DataFrame) -> Result<DataFrame>

Transform data using the fitted model

fn fit_transform(&mut self, data: &DataFrame) -> Result<DataFrame>

Fit and transform in one step