Abstract:The k nearest neighbor (KNN) classifier is one of the well-known instance-based classifiers. Nevertheless, the low efficiency in both running time and memory usage is a great challenge in the KNN classifier and its improvements due to noise and redundant samples. Although hybrid instance reduction approaches have been postulated as a good solution, they have the following issues: (a) adopted edition methods in existing hybrid instance reduction approaches are susceptible to harmful samples around the tested sa… Show more
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