Effect of Principle Component Analysis and Support Vector Machine in Software Fault Prediction
Journal Title: INTERNATIONAL JOURNAL OF COMPUTER TRENDS & TECHNOLOGY - Year 2014, Vol 7, Issue 3
Abstract
Machine Learning (ML) approaches have a great impact in fault prediction. Demand for producing quality assured software in an organization has been rapidly increased during the last few years. This leads to increase in development of machine learning algorithms for analyzing and classifying the data sets, which can be used in constructing models for predicting the important quality attributes such as fault proneness. Defective modules in software project have a considerable risk which reduces the quality of the software. This paper mainly addresses the software fault prediction using hybrid Support Vector Machine (SVM) classifier. We conduct a comparative study using the WEKA tool for three different levels of software metrics (package level, class level and method level) with hybrid SVM classifiers using feature selection techniques such as Principle Component Analysis (PCA). The experiments are carried out on the datasets such as NASA KC1 method level data set, NASA KC1 class level dataset and Eclipse dataset for package level metrics. The feature selection techniques evolved by experiments shows that Principle Component Analysis (PCA) with hybrid SVM performs better than other feature selection techniques.
Authors and Affiliations
A. Shanthini , G. Vinodhini , RM. Chandrasekaran
Keywords
Related Articles
- EP ID EP162698
- DOI -
- Views 102
- Downloads 0
Security in MANET Against DDoS Attack
Mobile ad-hoc network is a group of two or more devices or nodes with the capability of communication and networking. It is an infrastructure less network. Such network may operate by them or may be connected to a...
Securing ATM Using Graphical Password Authentication Scheme
In our day to day life ATMs are widely used and have brought so much relief to the financial world. Various problems were solved with the advent of these machines ranging from keeping the banking hall free of traffic wit...
An Efficient Web Prediction Model Using Modified Markov Model with ANN
Web prediction is a classification problem in which we try to predict the preceding set of Web pages in which a user may visit supported on the knowledge of the previously visited pages. While serving the Internet user’s...
Proactive Web Server Protocol for Complaint Assessment
Vulnerability Discovery with attack Injection security threats are increasing for the server software, when software is developed, the software tested for the functionality. Due to un-awareness of software vulnerabilitie...
An Approach for Load Balancing Among Multi-Agents to Protect Cloud Against DDos Attack
Cloud Computing is widely used technology in present era. Cloud Computing is mainly used for on demand services over the distributed servers. So it is necessary to manage the working load of participating servers for uni...