说明：  决策树一般都是自上而下的来生成的。每个决策或事件（即自然状态）都可能引出两个或多个事件，导致不同的结果，把这种决策分支画成图形很像一棵树的枝干，故称决策树。
(The generated tree may over-fit the training data –Too many branches, some may reflect anomalies due to noise or outliers –Result is in poor accuracy for unseen samples)