Improving Supervised Learning Classification Methods Using Multigranular Linguistic Modeling and Fuzzy Entropy.

IEEE Transactions on Fuzzy Systems(2017)

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摘要
Obtaining good classification results using supervised learning methods is critical if we want to obtain a high level of precision in the classification processes. The training data used for the learning process play a very important role in achieving this objective. Therefore, it is important to represent the data in a way that best expresses its meaning. For this purpose, we propose to apply lin...
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关键词
Pragmatics,Supervised learning,Computational modeling,Complexity theory,Training data,Entropy,Data models
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