Experimental Comparison of Different Problem Transformation Methods for Multi-Label Classification using MEKA
نویسندگان
چکیده
منابع مشابه
Feature Selection for Improving Multi-Label Classification using MEKA
The extensive dimensionality in multi-label classification can be overcome by selecting representative words that describe an instance and removing the redundant and insignificant ones. The popular technique of feature selection when applied reduces the size of the dataset and hence speeds up and improves the accuracy of the learning process of classification. This paper looks at the performanc...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2012
ISSN: 0975-8887
DOI: 10.5120/9622-4268