Instance-Based Learning Algorithms
Machine Learning
Structuralization of universes
Fuzzy Sets and Systems
Nearest prototype classification: clustering, genetic algorithms, or random search?
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Selecting Features and Objects for Mixed and Incomplete Data
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Finding Small Consistent Subset for the Nearest Neighbor Classifier Based on Support Graphs
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Object selection based on subclass error correcting for ALVOT
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Simultaneous features and objects selection for mixed and incomplete data
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Intelligent feature and instance selection to improve nearest neighbor classifiers
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
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In this paper we introduce a new method for selecting prototypes with Mixed Incomplete Data (MID) object description, based on an extension of the Nearest Neighbor rule. This new rule allows dealing with functions that are not necessarily dual functions of distances. The introduced compact set editing method (CSE) constructs a prototype consistent subset, which is also subclass consistent. The experimental results show that CSE has a very nice computational behavior and effectiveness, reducing around 50% of prototypes without appreciable degradation on accuracy, in almost all databases with more than 300 objects.