April 2017
Beginner to intermediate
358 pages
9h 30m
English
Content preview from Learning Data Mining with Python - Second Edition
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Real-time clusterings
The k-means algorithm can be iteratively trained and updated over time, rather than discrete analyses at given time frames. Cluster movement can be tracked in a number of ways—for instance, you can track which words are popular in each cluster and how much the centroids move per day. Keep the API limits in mind—you probably only need to do one check every few hours to keep your algorithm up-to-date.
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