Question

如何用ID3 p平决策树,而培训组中的例子很少。

我不能把它分为培训、鉴定和测试,这样就没有问题了。

是否有任何统计方法可以使用,或像这样的方法?

Answer 1

是的,如果数据交叉验证量低,就可用来培训和推算数据集。这一概念相当简单。你把数据分为N组,并用N-1对你的树木进行培训。最后,你将你作为你的跳板。然后,你拿到另一套N型飞机去除,也做同样的事情。在你离开所有文件之前,对此予以答复。这意味着你已经修建了N trees树。你们利用这些N树计算树木的最佳面积,然后用计算法对全部数据进行整套培训。这比我能在这里有效地描述更为复杂,但这里是关于如何使交叉验证适应ID3的文章。

Lots of research has been conducted on what the proper segmentation of cross validation, and it s been found N=10 gives the best results for the given extra processing time. Cross Validation increases your computation time by a lot (well N times), but when you have smaller amounts of data it can overcome the small number of samples. And since you don t have a lot of data that means using cross validation isn t that bad computationally.

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