November 2017
Beginner
286 pages
8h 13m
English
book
Statistics for Data Science
by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
Content preview from Statistics for Data Science
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Frequent item-setting
Building on the idea in the previous section (of finding frequent patterns) is frequent item-setting. To the data developer, by far the most applicable patterning concept is that of frequent item-setting or finding items that are found to be frequently a member of a group or set.
Using our stormy weather example from earlier in this chapter, one can envision the process of searching through a file or database of sales transactions, looking for the occasion (that is, the event) where milk, bread, and eggs were purchased together as one sale (or one set of products).
Frequent item setting also involves determining a minsup or minimum supported threshold to be used within an analysis. What this means is that the data scientist ...
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