SigmaIndex-SensorTests: Sigma-Index Sensor Dataset 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 sensor dataset tests compare sequential scan approach (iterating through all populations) with Sigma-Index approach. Generated diagrams are placed in the ./inst folder.

• SHC_TestCase_Sensors_SigmaIndex() - Processes the sensor dataset and places the results in the RDS files in the ./inst folder. These RDS files can be further used to generate diagrams.

• SHC_TestCase_Sensors_SigmaIndex_Display() - Generates diagrams from RDS files in the ./inst folder.

• prepareSensorDataset() - A function implicitly called by the SHC_TestCase_Sensors_SigmaIndex() function to download and prepare the sensor dataset. Since CRAN does not allow packages comprising big files, the sensor dataset is downloaded directly from the site (http://db.csail.mit.edu/labdata/labdata.html) and prepared (cleaned) by this function.

Usage

SHC_TestCase_Sensors_SigmaIndex(i, endingRound = 2000)
SHC_TestCase_Sensors_SigmaIndex_Display()
prepareSensorDataset()

Arguments

i	(integer) - A testing setting. Must be in {1,2,3}. If omitted, all settings are executed.
endingRound	(integer) - A number of data points processed from the sensor dataset in thousands, i.e., 2000 rounds = 2 million data points.

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.