Hydrometeor classification for radar based on ECOC-balanced random forest
To address the problem of hydrometeor classification with data imbalance condition,this paper proposes a hydrometeor classification method based on error correcting output code(ECOC)balanced random forest for dual-polarization weather radar.Firstly,the multiclass hydrometeor dataset is coded into multiple binary datasets,and then the binary datasets are balanced resampling with replacement to construct multiple classification and regression trees.Finally,all the classification and regression trees are used to jointly classify hydrometeors.The processing results of the measured data indicate that the proposed method can significantly improve the classification effect of minority classes while ensuring a high overall accuracy.
dual-polarization weather radarhydrometeor classificationdata imbalanceerror correcting output code(ECOC)balanced random forest
万方数据
维普
