Instance-Based Learning Algorithms
Machine Learning
Tolerating noisy, irrelevant and novel attributes in instance-based learning algorithms
International Journal of Man-Machine Studies - Special issue: symbolic problem solving in noisy and novel task environments
Foundations of Multidimensional and Metric Data Structures (The Morgan Kaufmann Series in Computer Graphics and Geometric Modeling)
Data Streams: Models and Algorithms (Advances in Database Systems)
Data Streams: Models and Algorithms (Advances in Database Systems)
Statistical Comparisons of Classifiers over Multiple Data Sets
The Journal of Machine Learning Research
Efficient instance-based learning on data streams
Intelligent Data Analysis
A review of instance selection methods
Artificial Intelligence Review
Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study
IEEE Transactions on Pattern Analysis and Machine Intelligence
The condensed nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Data reduction improves the efficiency of k-NN classifier on large datasets since it accelerates the classification process and reduces storage requirements for the training data. IB2 is an effective data reduction technique that selects some training items form the initial dataset and uses them as representatives (prototypes). Contrary to many other data reduction techniques, IB2 is a very fast, one-pass method that builds its reduced (condensing) set in an incremental manner. New training data can update the condensing set without the need of the "old" removed items. This paper proposes AIB2, a variation of IB2, which generates new prototypes instead of selecting them. AIB2 attempts to improve the efficiency of IB2 by positioning the prototypes in the center of the data areas they represent. The experimental study shows that AIB2 performs better than IB2.