Application of decision tree method to classification and prediction problems

Nowadays intellectualization of methods for data processing and data analysis is modern rapidly developing application known as Data Mining. This work is concerned with description of one of the Data Mining algorithm designed for solution of classification and prediction problems based on decision tree method. This method is also known as decision rule tree method or classification and regression tree method. The main feature of Data Mining is a combination of extended mathematical tools and novel achievements in the information technologies together with new hardware and software opportunities. The most methods were developed within to artificial intelligence theory. This work describes decision tree for solution classification problem of store employees under hand-building and by object-oriented programming language Python. We considered an example of decision tree for solution of Iris-Fisher data set classification problem, described hand-build tree and tree build by Python, and concern with implementation of decision trees over different software systems.