Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
The Entire Regularization Path for the Support Vector Machine
The Journal of Machine Learning Research
ROC curves and video analysis optimization in intestinal capsule endoscopy
Pattern Recognition Letters - Special issue: ROC analysis in pattern recognition
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The paper proposes a different approach to data modeling. Analogous to the rejection method, where the misclassifications are removed and manually evaluated, we focus here on difficult to distinguish cases for binary classification. Such cases are further explored and information granulation is conducted based on the idea to stretch out the interesting intervals. This refinement model adopts the concept from database theory where the nxn relations are resolved through additional internal attribute connections. We introduce an integration of target functions for such cases. The achieved experimental results from a test dataset are described and future work for user assistance in knowledge modeling is presented.