Decision Tree Ensemble Based Partial Label Learning Algorithm
YU Fei, ZHANG Minling
School of Computer Science and Engineering, Southeast University, Nanjing 210096 Key Laboratory of Computer Network and Information Integration of Ministry of Education,Southeast University, Nanjing 210096
Abstract To overcome the problem of the missing supervision information in partial label learning, a special splitting measure for the generation of decision tree is designed according to the property of partial label examples and the growth algorithm of decision tree is modified. In the proposed algorithm, bootstrap sampling is employed to construct multiple decision trees, and then the final prediction result is obtained by voting on the classification results of each decision tree. Experiments on artificial datasets and real-world datasets validate the good performance of the proposed algorithm.
Fund:Supported by National Natural Science Foundation of China (No.61573104,61222309), MOE Program for New Century Excellent Talents in University (No. NCET-13-0130)
About author:: (YU Fei， born in 1990， master student. His research interests include machine learning and data mining.) (ZHANG Minling(Corresponding author)， born in 1979， Ph.D.， professor. His research interests include machine learning and data mining.)
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2016, Vol. 29 
