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A reconciliation between cosine similarity and Euclidean distance in individual decision-making problems

Author

Listed:
  • Saptarshi Mukherjee

    (Indian Institute of Technology Delhi)

  • Ruhi Sonal

    (Indraprastha Institute of Information Technology Delhi)

Abstract

Although both Euclidean distance and cosine similarity are widely used as measures of similarity, there is a lack of clarity as to which one is a better measure in applications such as machine learning exercises and in modeling consumer behavior. In this note we establish a reconciliation between these two approaches in an individual decision-making problem with a reference point.

Suggested Citation

  • Saptarshi Mukherjee & Ruhi Sonal, 2023. "A reconciliation between cosine similarity and Euclidean distance in individual decision-making problems," Indian Economic Review, Springer, vol. 58(2), pages 427-431, December.
    • Handle: RePEc:spr:inecre:v:58:y:2023:i:2:d:10.1007_s41775-023-00206-8
    DOI: 10.1007/s41775-023-00206-8
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    Keywords

    Choice; Cosine similarity; Euclidean distance;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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