Clustering multiple data

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Data Science 101 slides

 

Review slides 296 – 327 for the following topics:

Working with binary data – cosine distance
Clustering binary data – spherical k-means
Assessing quality of spherical k-means clustering
Interpreting clusters of binary data and making recommendations
Pitfalls of clustering

Complete the following exercises:

Exercise set 3 – Clustering many attributes

Complete Concept review 4: implementation of clustering in the Assessment tab to complete this lesson

[LF_dataworld]

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