SigmaIndex-SyntheticTests: Sigma-Index Synthetic Testing Procedures

In dkrleza/SHClus: Statistical Hierarchical Clustering

Description

Sigma-Index is a statistical organizing structure aiming to improve query and processing times for statistical algorithms, when searching space comprising statistical populations. These synthetic tests compare sequential scan approach (iterating through all populations) with Sigma-Index approach. Generated diagrams are placed in ./inst folder.

• SHC_TestCase_ClustersAndOutliers_SigmaIndex() - Generates comparison diagrams for synthetically generated set of clusters and outliers. This is the basic testing of the Sigma-Index improvements and usability.

• SHC_TestCase_ClustersAndOutliers_SigmaIndex_Theorems() - Generates computational cost reduction histograms that experimentally proves theorems about balacing the Sigma-Index DAG.

Usage

SHC_TestCase_ClustersAndOutliers_SigmaIndex(n=100000)
SHC_TestCase_ClustersAndOutliers_SigmaIndex_Theorems()

Arguments

n	(integer) - A number of data points generated for the test.

Author(s)

Dalibor Krleža

References

[1] Krleža D, Vrdoljak B, and Brčić M, Statistical hierarchical clustering algorithm for outlier detection in evolving data streams, Machine Learning, Sep. 2020

dkrleza/SHClus documentation built on Feb. 25, 2021, 10:30 p.m.