adaboost matlab 程序
代码说明：
Description This a classic AdaBoost implementation, in one single file with easy understandable code. The function consist of two parts a simple weak classifier and a boosting part: The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes -1 and 1 The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier" . Training mode: [estimateclass,model]=adaboost("train",datafeatures,dataclass,itt) Apply mode: estimateclass=adaboost("apply",datafeatures,model) inputs/outputs: datafeatures : An Array with size number_samples x number_features dataclass : An a
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