Survey on Different Machine Learning Techniques for Software Effort Estimation
نویسندگان
چکیده
منابع مشابه
A Survey of Software Effort Estimation Techniques Using Machine Learning
Software effort estimation is an aspect of software engineering involving evaluation of numerous different changing factors related to the creation of a system. Historically, estimation methods have relied on construction cost models (COCOMO) and function point analysis (FPA) to deliver accurate estimation values. We explored recently published works from 2016, describing the incorporation of m...
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Accurate estimation of software development effort is a very difficult job.Both under estimation as well as over estimation can lead to serious consequences. So its very important to find a technique which can yield accurate results for software effort estimation. Here in our paper we have evaluated various machine learning techniques for software effort estimation like bagging, decision trees,...
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Software project management is one of the significant activates in the software development process. Software Development Effort Estimation (SDEE) is a challenging task in the software project management. SDEE is an old activity in computer industry from 1940s and has been reviewed several times. A SDEE model is appropriate if it provides the accuracy and confidence simultaneously before softwa...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2014
ISSN: 0975-8887
DOI: 10.5120/16748-6902