Interactive Inductive Learning Based Classification System
Proceedings of the IADIS International Conference Intelligent Systems and Agents 2011 2011
Ilze Birzniece

Inductive learning system learns classification from training examples and uses induced rules for classifying new instances. As the classification tasks are getting more complicated, a classifier may meet difficulties in class prediction. To improve predictive accuracy of the inductive learning classifier, collaborative approach between a machine and human expert would be useful. The proposed interactive inductive system in uncertain conditions can ask for human advice and improve its performance with a rule derived from this interaction. Interactive inductive learning based classification system is proposed to assist in a study course comparative analysis.


Atslēgas vārdi
Inductive learning, human-computer interaction, study course comparison

Birzniece, I. Interactive Inductive Learning Based Classification System. No: Proceedings of the IADIS International Conference Intelligent Systems and Agents 2011, Itālija, Rome, 24.-26. jūlijs, 2011. Rome: IADIS Press, 2011, 112.-116.lpp. ISBN 9789728939410.

Publikācijas valoda
English (en)
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