Abstract: Memory-based classification techniques are commonly used for modeling recommendation problems. They rely on the intuition that similar users and/or items behave similarly, facilitating ...
To complete the task of automatic recognition and classification of thyroid nodules and solve the problem of high classification error rates when the samples are ...
An Efficient Slime Mould Algorithm Combined With K-Nearest Neighbor for Medical Classification Tasks
Abstract: Growing science and medical technologies have produced a massive amount of knowledge on different scales of biological systems. By processing various amounts of medical data, these ...
The k nearest neighbor (kNN) approach is a simple and effective nonparametric algorithm for classification. One of the drawbacks of kNN is that the method can only give coarse estimates of class ...
ABSTRACT: In this paper we introduced Tanimoto based similarity measure for host-based intrusions using binary feature set for training and classification. The k-nearest neighbor (kNN) classifier has ...
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