Extensions of the Separate-and-Conquer Multilabel Rule Learner
| Type of publication: | Mastersthesis |
| Citation: | ba:salem |
| Type: | Bachelor Thesis |
| Year: | 2017 |
| Month: | August |
| 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 Mencía 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. |
| Userfields: | betreuer={ELM} |
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