Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Accuracy Tuning on Combinatorial Neural Model
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Optimizations of the Combinatorial Neural Model
SBRN '98 Proceedings of the Vth Brazilian Symposium on Neural Networks
Learning in the combinatorial neural model
IEEE Transactions on Neural Networks
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Human beings live in a structural, natural, social, cultural, and linguistic coupling and continuously regenerate the processes that organize themselves. The proactive agent in relation to the social environment was studied. The proactivity was taken as the possibility of transforming society from the perspective of social inequality. In this sense, it was studied the self-perception of the young in relation to willingness for social proactivity. The Combinatorial Neural Model was applied to recognize patterns from a socioeconomic survey and texts written during the selection for entering the undergraduate courses aiming at understanding the student view on her/his social role. The whole process was conducted under the CRISP-DM guidelines. The model succeeded in identifying differents rules that characterize non-proactive students. Results show to be useful for subsidizing educators and managers of educational institutions in decision making with information on students' profile.