Multi-view programming learning to obtain interpretable classifiers for semi-supervised contexts

HIGHLIGHTS

  • who: Rule-based classification and colleagues from the Computing and Numerical Analysis Department, University of Cu00f3rdoba, Cu00f3rdoba, Spain have published the Article: Multi-view Programming Learning to Obtain Interpretable Classifiers for Semi-supervised Contexts, in the Journal: (JOURNAL) of 29/01/2019
  • what: The authors conclude that the multi-view learning methodology is certainly getting benefit from the presence of unlabeled patterns, although slightly with regard to the model with just one view, and that two views seem to perform slightly better than more views, given that in the case , more views introduces noise in . . .

     

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