2.4 DS: Jaccard Coefficient or Index or Similarity

#JaccardCoefficient #Jaccard #similarity #MachineLearning #DataScience #DataMining #ComputingForAll
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The high similarity between a pair of points indicates that the points are nearby. Low similarity indicates a large distance. Literature covers several similarity measures. In this video we talk about Jaccard coefficient or index or similarity.

Jaccard index/coefficient/similarity is generally computed between two sets of items. It is a ratio of commonality between the sets over all the items. If X and Y are two sets, then the Jaccard index between two sets is computed using the ratio of the size of the intersection and the size of the union of the two sets.

Jaccard index can be computed between two vectors too. Jaccard index computed between two vectors/data points/objects is called a weighted Jaccard index.

Here is a video on the Python code for computing Jaccard Similarity:
https://youtube.com/shorts/bjKcBpctBmk?feature=share

For examples and more similarity measures visit the page below:
https://computing4all.com/courses/introductory-data-science/lessons/similarity-measures/

Visit the page with all the data science materials we have developed: https://computing4all.com/courses/introductory-data-science/

Thank you.

Dr. Shahriar Hossain
https://computing4all.com

#JaccardSimilarity #JaccardIndex

Видео 2.4 DS: Jaccard Coefficient or Index or Similarity канала Computing For All