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This paper offers a thorough comparison of several clustering techniques using a range of datasets. The main goal is to assess how well algorithms such as K-Means, Hierarchical Clustering, and DBSCAN work in various contexts, such as road service routing, power systems, educational data mining, and more. The “Economic Freedom Index 2023” dataset from “The Heritage Foundation” is used in the study to compare various algorithms, taking into account variables including government honesty, judicial efficacy, and property rights. The findings underscore the importance of selecting the appropriate algorithm for efficient data-driven decision-making by pointing out the superiority of some algorithms in particular scenarios.

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Comparative Analysis of Clustering Algorithms on Economic Freedom Index

  • 会议论文

  • 发表日期：

    2026年

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  • Iram Naim,
  • Shreyanshi Dixit,
  • Mrittika Chandra

摘要

This paper offers a thorough comparison of several clustering techniques using a range of datasets. The main goal is to assess how well algorithms such as K-Means, Hierarchical Clustering, and DBSCAN work in various contexts, such as road service routing, power systems, educational data mining, and more. The “Economic Freedom Index 2023” dataset from “The Heritage Foundation” is used in the study to compare various algorithms, taking into account variables including government honesty, judicial efficacy, and property rights. The findings underscore the importance of selecting the appropriate algorithm for efficient data-driven decision-making by pointing out the superiority of some algorithms in particular scenarios.