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@MASTERSTHESIS{ba:salem,
    author = {Salem, Borhan Youssef},
     month = aug,
     title = {Extensions of the Separate-and-Conquer Multilabel Rule Learner},
      type = {Bachelor Thesis},
      year = {2017},
    school = {TU Darmstadt, Knowledge Engineering Group},
       url = {/lehre/arbeiten/bachelor/2017/Salem_Borhan-Youssef.pdf},
  abstract = {Multi-label classification is the task in Machine Learning to assign more than one label to an instance.
Opposite to the single-label classification problem, where only a binary or a multi-class can be assigned to
an instance, dependencies may exist between different labels in a multi-label problem. These dependencies
can be used to improve the classification task and help to better understanding the multi-label dataset. A
Separate-and-Conquer Multi-Label Rule Learner was proposed 2016 by Eneldo Loza Menc{\'{\i}}a and Frederik
Janssen, that learn multi-label dependency and use them in the classification task. In this work we made
some extensions of the proposed algorithm and evaluate them.},
betreuer={ELM}
}