Classification method of unbalanced data set

The invention provides a classification method of an unbalanced data set, and the method comprises the steps of obtaining the unbalanced data set which comprises a positive data set and a negative data set; performing sampling processing on the positive data set and the negative data set to obtain a new data set; and training a SVM classifier by using the new data set to obtain a classification model, and classifying the to-be-tested data set by using the classification model. According to the classification method, the classification hyperplanes of the positive data set and the negative dataset are obtained firstly, then the undersampling is conducted on the positive data set according to the classification hyperplanes, and the oversampling is conducted on the negative data set accordingto the classification hyperplanes, so that the classification accuracy and efficiency are improved. 本发明提供一种非平衡数据集的分类方法，该方法包括获取非平衡数据集，所述非平衡数据集包括正类数据集和负类数据集；对正类数据集和负类数据集进行采样处理，获得新的数据集；利用新的数据集对SVM分类器进行训练，获得分类模型，用分类模型对待测数据集进行分类。该