1 MSc student of computer engineering – software, Pooyandegan Danesh Institution of Higher Education, Chalus, Iran

2 Full time science Committee member, Islamic Azad University of chalus, Chalus, Iran


Nowadays, data mining is one of the most significant issues. One field of data mining is a mixture of computer science and statistics which is considerably limited due to increase in digital data and growth of computational power of computers. One of the domains of data mining is the software cost estimation category. In this article, classifying techniques of learning algorithm of machine and COCOMO model as the most common estimation model of software costs are presented. Then, the analysis method of principal component approach is presented. This article presents a method to improve the performance of software cost estimation is suitable. Moreover, the basic data set is decreased and is turned into a new collection by using this method. Among the features, the best are extracted. The algorithms of several classifications are assessed by applying this method. Finally, the evidence for accuracy of our claims in terms of increase in estimation accuracy of software costs is presented.


Main Subjects

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