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author:

Huang, Ziheng (Huang, Ziheng.) [1] | Zhang, Yichun (Zhang, Yichun.) [2] | Yu, Tianrun (Yu, Tianrun.) [3]

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EI Scopus

Abstract:

KNN is an important part of classification algorithms in machine learning, which has been extensively employed in various fields. In this research, we proposed a Lp Norm-Based Local Means k-Nearest Neighbor Classification with Feature Reduction. We extend the original Euclidean distance formula, and obtain the distance calculation formula based on P-value. Then classify and predict the data set after dimension reduction. In the experiment, we verified the effectiveness and superiority of our method by setting different k values in KNN, LMKNN and the classification accuracy obtained by our methodology (PLMKNN). © 2023 IEEE.

Keyword:

Classification (of information) Learning algorithms Machine learning Motion compensation Nearest neighbor search

Community:

  • [ 1 ] [Huang, Ziheng]School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang; 621010, China
  • [ 2 ] [Zhang, Yichun]Maynooth International Engineering College, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Yu, Tianrun]School of Information and Mechatronics Engineering, Shanghai Normal University, Shanghai; 201418, China

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Year: 2023

Page: 376-381

Language: English

Cited Count:

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ESI Highly Cited Papers on the List: 0 Unfold All

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Chinese Cited Count:

30 Days PV: 3

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