问题描述
我正在尝试实现一个使用AdaBoost算法的应用程序.我知道AdaBoost使用一组弱分类器，但是我不知道这些弱分类器是什么.您可以通过示例向我解释一下，并告诉我是否必须创建自己的弱分类器，还是应该使用某种算法?
I am trying to implement an application that uses AdaBoost algorithm. I know that AdaBoost uses set of weak classifiers, but I don't know what these weak classifiers are. Can you explain it to me with an example and tell me if I have to create my own weak classifiers or I'm suppoused to use some kind of algorithm?
推荐答案
当我使用AdaBoost时，我的弱分类器基本上是每个数据属性的阈值.这些阈值必须具有超过50％的性能，否则将是完全随机的.
When I used AdaBoost, my weak classifiers were basically thresholds for each data attribute. Those thresholds need to have a performance of more than 50%, if not it would be totally random.
以下是有关Adaboost以及如何计算这些弱分类器的精彩演讲: http://www.cse.cuhk.edu.hk /~lyu/seminar/07spring/Hongbo.ppt
Here is a good presentation about Adaboost and how to calculate those weak classifiers:http://www.cse.cuhk.edu.hk/~lyu/seminar/07spring/Hongbo.ppt
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