kneighbors_distance_docall: K-Nearest neighbors algorithm to compute an anomaly score

In AnomalyScore: Anomaly Scoring for Multivariate Time Series

K-Nearest neighbors algorithm to compute an anomaly score

Description

The method obtain a distance matrix and find the K-nearest neighbors of each series and sum their distances in the neighborhood. The sum is defined as the anomaly score, the series with higher scores implies their neighbors are far away and such a series is a potential outlier

Usage

kneighbors_distance_docall(knn, distance, dparams)

Arguments

knn	number of nearest neighbors to consider for the anomaly score
distance	function name of the available distance matrices
dparams	a list with all the parameters for the distance matrix

Value

A list of two elements with the anomaly scores and the distance matrix

See Also

Guillermo Granados, and Idris Eckley. "Electricity Demand of Buildings Benchmarked via Regression Trees on Nearest Neighbors Anomaly Scores"

Examples

X=matrix( rnorm(2000), ncol=10  )
distance=distance_matrix_coherence
dparams=list(unit=X, span1=2, span2=2, period = 5 )
knn=5
kneighbors_distance_docall(knn,distance, dparams)

AnomalyScore documentation built on April 4, 2025, 3:13 a.m.