This paper is published in Volume-6, Issue-4, 2020
Area
Computer Science And Engineering
Author
Megha Saloni, Sucheta
Org/Univ
Yamuna Group of Institutions Engineering and Technology, Yamuna Nagar, Haryana, India
Keywords
Software, Defect, Estimation, Features, Machine Learning
Citations
IEEE
Megha Saloni, Sucheta. Review on software defect prediction with role of Machine Learning and Feature Selection, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Megha Saloni, Sucheta (2020). Review on software defect prediction with role of Machine Learning and Feature Selection. International Journal of Advance Research, Ideas and Innovations in Technology, 6(4) www.IJARIIT.com.
MLA
Megha Saloni, Sucheta. "Review on software defect prediction with role of Machine Learning and Feature Selection." International Journal of Advance Research, Ideas and Innovations in Technology 6.4 (2020). www.IJARIIT.com.
Megha Saloni, Sucheta. Review on software defect prediction with role of Machine Learning and Feature Selection, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Megha Saloni, Sucheta (2020). Review on software defect prediction with role of Machine Learning and Feature Selection. International Journal of Advance Research, Ideas and Innovations in Technology, 6(4) www.IJARIIT.com.
MLA
Megha Saloni, Sucheta. "Review on software defect prediction with role of Machine Learning and Feature Selection." International Journal of Advance Research, Ideas and Innovations in Technology 6.4 (2020). www.IJARIIT.com.
Abstract
Machine Learning approaches are helpful & have well-tried to be helpful in resolution issues & technical problems that lack data. In most cases, the package domain issues may be characterized as a method of learning that depends on the assorted circumstances and changes of the technical issue being addressed in keeping with the principles of machine learning, a prophetic model is made by exploitation machine learning approaches and classified into defective and non-defective modules. Machine learning techniques facilitate developers to retrieve helpful data when the classification of kinds of technical problems being addressed in an exceedingly specific field. This successively permits them to analyze knowledge from totally different views, which may be used because of the formation base of constructive concepts & varied techniques to handle the technical problems. Machine learning techniques are well-tried to be helpful within the detection of package bugs