| Data Mining is a process which reveals new relationships, trends and patterns through careful analysis of substantial data. It is an important topic of Information Technology research field. Data Mining is a process which extracts implicit, unknown, non-trivial and potential information or pattern from a large database or data warehouse. It combines with theory and technology of database, artificial intelligence, machine learning and other fields. Classification analysis of Data Mining technology is an important direction of research. Classification algorithm of Data Mining is most widely used in commercial, while decision tree algorithm is a core technology of classification algorithm. In decision tree algorithm, the famous one is ID3 algorithm which was presented by Quinlan in 1986. The importance of this paper is to study ID3 algorithm of decision tree and its improvement.First of all, the paper introduced ID3 algorithm. Then, further research on ID3 algorithm is done. ID3 algorithm has two major drawbacks: one is that using log is not easy to calculate. The other: algorithm selection is often biased in favor of the more property values, but property values of more property are not always optimal. In order to solve the problem of complex computing, the paper uses Maclaurin formula. ID3 simplified algorithm is proposed based on ID3 algorithm in the paper, so that the computing becomes easy. For solving the other problem, binary tree storage of ID3 simplified algorithm is put forward based on ID3 algorithm in the paper by using binary tree of data structure. Then, their decision trees emerged through the calculation of the same examples which use the same training set.Finally, the paper does a comparative study of the decision trees of different algorithms in order to sum up the conclusions: binary tree storage of ID3 simplified algorithm is proved more efficient through comparing ID3 algorithm with ID3 simplified algorithm and binary tree storage of ID3 simplified algorithm. |
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