Evaluation of sequential feature selection in improving the K-nearest neighbor classifier for diabetes prediction
Rajkumar Govindarajan,
Vidhyashree Balaji,
Jayanthi Arumugam
et al.
Abstract:The K-nearest neighbor (KNN) classifier employs distance metrics to measure the distance between the test instance and the samples used in training. With smaller samples, the KNN classifier achieves higher accuracy with low computational time. However, computing the distance between the test instance and all training samples to determine the class of the test instance requires higher computational time for a high-dimensional dataset. This research employs sequential feature selection (SFS) to select the optima… Show more
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