9 Distance Measures in Data Science

 By Medium - 2021-02-01

Description

Exploring the advantages and pitfalls of 9 common distance measures used in Machine Learning applications.

Summary

  • Daily Read 9 Distance Measures in Data Science The advantages and pitfalls of common distance measures Many algorithms, whether supervised or unsupervised, make use of distance measures.
  • Moreover, you can also use Hamming distance to measure the distance between categorical variables.
  • In practice, it is the total number of similar entities between sets divided by the total number of entities.
  • Intuition is important in distance measures as it allows for better usage of the metric without v The Jaccard index (or Intersection over Union) is a metric used to calculate the similarity and diversity of sample sets.

 

Topics

  1. Backend (0.26)
  2. NLP (0.17)
  3. Database (0.13)

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