Abstract
Pointing to the computational complexity to find the minimum distance in the nearest feature line (NFL) classification algorithm, the nearest neighbor search methods with Full Search (FS), Partial Distortion Search (PDS), Absolute Error Inequality (AEI) and Equal-average Nearest Neighbor Search (ENNS) is used to evaluate the calculated performance on NFL. The experimental results demonstrate that the computational complexity on NFL using these search techniques is different and some of the nearest neighbor search methods could improve the calculated performance on finding out the minimum distance applied in the NFL classification.
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