Presented a method for estimating the cost of software using PCA to reduce the size and with the help of data mining

These days, data mining one of the most significant issues. One field 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 computer. 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 were presented. Then the analysis method of principal component approach are presented. This article shows that the method to increase the accuracy of software cost estimation is suitable. Then, the basic data set was decreased and was turned into a new collection by using this method. Among the features, the best were extracted. The algorithm of several classifications were assessed by applying this method. Finally, the evidence for accuracy of our claims in terms of increase in estimation accuracy of software costs was presented.