SOFTWARE PERFORMANCE PREDICTION USING RANDOM FOREST BASED REGRESSION ANALYSIS

Abstract

 The evaluation of various software quality metrics like performance, reliability, and response time are done usingquantitative techniques and it is essential for component based software applications. In this paper the performanceof the software application is predicted using regression analysis. In general, the trend analysis technique isemployed to predict the performance of the software system. The proposed method in this paper will help theusers of the software system to predict whether it satisfies their requirements for a set of features selected by them.The performance of the software gets vary based on the features selected by the users. The features may interactwith other feature and degrade the overall performance of the system. The performance prediction is carried outusing the Random forest which is capable of handling thousands of input variables without deleting the variables.Also it offers an experimental method for the detection of the feature interactions.

Authors and Affiliations

R. Sathya*

Keywords

Related Articles

DROWSY DRIVER DETECTION SYSTEM

A Drowsy Driver Detection System is an Image processing based system. This system is developed using a nonintrusive machine vision based concepts. In this system, there is a camera that will be continuously monitoring t...

Distribution and Ecology of the Recent Benthic Foraminifera from the sediments of Adyar River, Chennai, Tamilnadu, India

Micropalaeontological investigation has been carried out, for the first time to study the systematic of recent Benthic Foraminifera from the Adyar River, Chennai, Tamilnadu, India, Totally 20 sediment samples were collo...

 Efficient Biometric Iris Recognition Using Hough Transform

 The demand for an accurate biometric system that provides reliable identification and verification of an individual has increased over the years. A biometric system that provides reliable and accurate identificati...

 Removal of Heavy Metal Ions from Wastewater by Carbon Nanotubes (CNTs)

 Advent of nanotechnology has introduced us with new generation of adsorbents such as carbon nanotubes (CNTs) which have aroused widespread attention due to their outstanding ability for the removal of various ino...

 SOLUTION FOR FUZZY DIFFERENTIAL EQUATIONS USING FOURTH ORDER RUNGE-KUTTA METHOD WITH EMBEDDED HARMONIC MEAN

 In this paper, an attempt has been made to determine a numerical solution for the first order fuzzy differential equations by using fourth order Runge-kutta embedded harmonic mean. The accuracy and applicability o...

Download PDF file
  • EP ID EP138982
  • DOI 10.5281/zenodo.160860
  • Views 60
  • Downloads 0

How To Cite

R. Sathya* (30).  SOFTWARE PERFORMANCE PREDICTION USING RANDOM FOREST BASED REGRESSION ANALYSIS. International Journal of Engineering Sciences & Research Technology, 5(10), 288-293. https://europub.co.uk/articles/-A-138982