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Asked by Suchitra Last Modified
Answer 
Ashis Sahu
Transforming Data into Actionable Insights: Experienced Data Scientist with FMCG knowledge
Imagine you have a group of friends, and you want to categorize them based on their movie preferences. Each friend can prefer different genres, like Action, Comedy, Drama, etc. Let's say you have the following data:
| Friend | Favorite Genre 1 | Favorite Genre 2 |
|---------|-------------------|------------------|
| Alice | Action | Comedy |
| Bob | Drama | Comedy |
| Carol | Action | Drama |
| Dave | Comedy | Action |
| Eve | Drama | Action |
Fuzzy K-Modes helps in grouping friends based on their movie preferences, allowing for overlaps where a friend can belong to multiple groups to varying degrees. This approach is particularly useful when preferences are not clear-cut, and people can like more than one genre.
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