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The present work expounds a preliminary work of a genetic programming algorithm to deal with multi-label classification problems. The algorithm uses Gene Expression Programming and codifies a classification rule into each individual. A niching technique assures diversity in the population. The final classifier is made up by a set of rules for each label that determines if a pattern belongs or not...
Virtual learning environments (VLE) offer a continuous learning system where information, resources and experiences are always available. Currently, these systems are widely used as a support for face to face classes. In this sense, they make easier the communication with students and maintain activities and resources for the subject. This paper presents the design and development of a subject using...
This paper presents our experience in a programming course unit during its first year of EHEA. The course unit features described are the students' profile, teaching methodology and assessment criteria. The virtualisation process and the self-evaluation carried out are presented, concluding our analysis with a set of discussions and recommendations to improve our next teaching course.
There are numerous problems of increasing significance where a pattern can have several classes simultaneously associated. This kind of problems, usually called multi-label problems, should be tackled with specific techniques in order to generate models more accurate than those obtained with classical classification algorithms. This work presents the adaptation of the J48 algorithm to multi-label...
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