Learning from multi-label data with interactivity constraints: An extensive experimental study
نویسندگان
چکیده
منابع مشابه
Learning from multi-label data with interactivity constraints: An extensive experimental study
Interactive classification aims at introducing user preferences in the learning process to produce individualized outcomes more adapted to each user’s behaviour than the fully automatic approaches. The current interactive classification systems generally adopt a singlelabel classification paradigm that constrains items to span one label at a time and consequently limit the user’s expressiveness...
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ژورنال
عنوان ژورنال: Expert Systems with Applications
سال: 2015
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2015.03.006