"数据挖掘中的决策树算法比较与应用研究"

With the rapid development of Information Technology, people are facing much more work load in dealing with the accumulated mass data. Data mining technology is also called the knowledge discovery in databases, which is a process of effectively and implicitly extracting previously unknown, potentially valuable information from large-scale databases. One of the important classification methods in data mining is the decision tree algorithm. The various algorithms based on decision trees have their own advantages in terms of execution speed, scalability, interpretability of the output results, and accuracy of classification prediction, and have been widely applied in various fields. There are already many mature systems in fields such as speech recognition, pattern recognition, and expert systems. This paper focuses on the study and comparison of several typical decision tree algorithms, and provides examples of their applications. Keywords: Data Mining; Decision Tree; Comparison.