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adaboos
- 当弱分类器算法使用简单的分类方时,boosting的效果明显地统一地比bagging要好.当弱分类器算法使用C4.5时,boosting比bagging较好,但是没有前者的比较来得明显.-When the weak classifier algorithm using simple classification method, boosting the effect clearly uniformly better than bagging. When the weak classifier
classificiation-algorithm-overview
- 机器学习领域经典分类算法综述,包括Decision Tree(ID3、C4.5(C5.0)、CART、PUBLIC、SLIQ和SPRINT算法),三种典型贝叶斯分类器(朴素贝叶斯算法、TAN算法、贝叶斯网络分类器),k-近邻 、 基于数据库技术的分类算法( MIND算法、GAC-RDB算法),基于关联规则(CBA:Classification Based on Association Rule)的分类(Apriori算法),支持向量机分类,基于软计算的分类方法(粗糙集(rough set)、遗传
adaboost
- Now, you ought to implement the AdaBoost.M1 and AdaBoost.M2 algorithms. These algorithms are two versions of the AdaBoost algorithm for handling the Problems with more than two classes. You must first read the paper “Experiments with a New Boosti