Probability-Based Distance Function for Distance-Based Classifiers
- Cezary Dendek,
- Jacek Mańdziuk
In the paper a new measure of distance between events/observations in the pattern space is proposed and experimentally evaluated with the use of k-NN classifier in the context of binary classification problems. The application of the proposed approach visibly improves the results compared to the case of training without postulated enhancements in terms of speed and accuracy. Numerical results are very promising and outperform the reference literature results of k-NN classifiers built with other distance measures.
- Record ID
- Alippi Cesare, Cesare Alippi Polycarpou Marios, Marios Polycarpou Panayiotou Christos Christos Panayiotou [et al.] (eds.): Artificial Neural Networks – ICANN 2009, Lecture Notes In Computer Science, no. 5768, 2009, Springer Berlin Heidelberg, ISBN 978-3-642-04273-7, 978-3-642-04274-4
- Keywords in English
- Artificial Intelligence (incl. Robotics), Computation by Abstract Devices, Data Mining and Knowledge Discovery, Neurosciences, pattern recognition, Simulation and Modeling
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