Computer Science ›› 2015, Vol. 42 ›› Issue (5): 106-108.doi: 10.11896/j.issn.1002-137X.2015.05.021

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Pre-processing Method of Multi-label Classification Based on kNN

XU Xiao-dan, YAO Ming-hai, LIU Hua-wen and ZHENG Zhong-long   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Multi-label learning is a new field in machine learning.In order to improve the multi-label classification precision,a new kNN method was used to remove the noise labels.First,a normal distribution is discovered by analyzing the characteristics of multi-label datasets,and then the high quality datasets are generated by changing the value of noisy labels to their k-Nearest Neighbors.In the experiments,six kinds of multi-label classification methods were tested on MULAN with new datasets.Compared to the primal datasets,the classification precision based on new datasets is better.Research results show this method is suitable for the data set which has a regular distribution.

Key words: Multi-label,Classification,Normal distribution,Pretreatment,kNN

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