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A novel nearest neighbors algorithm based on power muirhead mean

Published: 16 September 2024 Publication History

Abstract

This paper introduces the innovative Power Muirhead Mean K-Nearest Neighbors (PMM-KNN) algorithm, a novel data classification approach that combines the K-Nearest Neighbors method with the adaptive Power Muirhead Mean operator. The proposed methodology aims to address the limitations of traditional KNN by leveraging the Power Muirhead Mean for calculating the local means of K-nearest neighbors in each class to the query sample. Extensive experimentation on diverse benchmark datasets demonstrates the superiority of PMM-KNN over other classification methods. Results indicate statistically significant improvements in accuracy on various datasets, particularly those with complex and high-dimensional distributions. The adaptability of the Power Muirhead Mean empowers PMM-KNN to effectively capture underlying data structures, leading to enhanced accuracy and robustness. The findings highlight the potential of PMM-KNN as a powerful and versatile tool for data classification tasks, encouraging further research to explore its application in real-world scenarios and the automation of Power Muirhead Mean parameters to unleash its full potential.

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    Published In

    cover image Intelligent Decision Technologies
    Intelligent Decision Technologies  Volume 18, Issue 3
    2024
    963 pages
    ISSN:1872-4981
    EISSN:1875-8843
    Issue’s Table of Contents

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    IOS Press

    Netherlands

    Publication History

    Published: 16 September 2024

    Author Tags

    1. Machine learning
    2. K-Nearest neighbors
    3. power muirhead mean

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