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[AI-NN-PR] SMOTEBoost DL : 0: 分类非平衡数据的SMOTEboost算法-This code implements SMOTEBoost. SMOTEBoost is an algorithm to handle class imbalance problem in data with discrete class labels. It uses a combination of SMOTE and the standard boosting procedure AdaBoost to better model the minority class by providing the learner not only with the minority class examples that were misclassified in the previous boosting iteration but also with broader representation of those instances (achieved by SMOTE). Since boosting algorithms give equal weight to all misclassified examples and sample from a pool of data that predominantly consists of majority class, subsequent sampling of the training set is still skewed towards the majority class. Thus, to reduce the bias inherent in the learning procedure due to class imbalance and to increase the sampling weights of minority class, SMOTE is introduced at each round of boosting. Introduction of SMOTE increases the number of minority class samples for the learner and focus on these cases
Date : 2025-12-17 Size : 5.37mb User : 贾建华