决策树算法在分类预测中的应用与优化

The Optimization and Application of the Decision Tree Algorithm in the Classification Prediction

决策树是一类常见的机器学习方法,具有属性结构和较好的分类预测能力,可以根据既定规则完成基本的决策任务。本文阐述了决策树算法的基本思想,并以某银行信贷问题为例,分析了决策树算法在应用中遇到的一些问题,最后给出了性能调优方案。

Decision tree is a kind of common method in machine learning, it is with an attribute structure and better ability to classify and predict and it can complete basic decision tasks according to the given rules. The paper firstly expounded the basic thoughts and then analyzed some problems in the application of the decision tree algorithm taking a bank credit as case to obtain the performance tuning scheme in the end.