April 2016
Beginner to intermediate
384 pages
8h 36m
English
Content preview from Practical Data Analysis CookbookBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Building fuzzy clustering model with c-means
K-means and Mean Shift clustering algorithms put observations into distinct clusters: an observation can belong to one and only one cluster of similar samples. While this might be right for discretely separable datasets, if some of the data overlaps, it may be too hard to place them into only one bucket. After all, our world is not just black or white but our eyes can register millions of colors.
The c-means clustering model allows each and every observation to be a member of more than one cluster and this membership is weighted: the sum of all the weights across all the clusters for each observation must equal 1.
Getting ready
To execute this recipe, you will need pandas and the Scikit-Fuzzy module. The ...
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