June 2011
Beginner to intermediate
744 pages
25h 11m
English
Content preview from Data Mining: Concepts and Techniques, 3rd Edition
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12.10 Exercises
12.1 Give an application example where global outliers, contextual outliers, and collective outliers are all interesting. What are the attributes, and what are the contextual and behavioral attributes? How is the relationship among objects modeled in collective outlier detection?
12.2 Give an application example of where the border between normal objects and outliers is often unclear, so that the degree to which an object is an outlier has to be well estimated.
12.3 Adapt a simple semi-supervised method for outlier detection. Discuss the scenario where you have (a) only some labeled examples of normal objects, and (b) only some labeled examples of outliers.
12.4 Using an equal-depth histogram, design a way to assign an object ...
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