Consider the following definition of an anomaly: An anomaly is an object that is unusually influential in the creation of a data model.
(a) Compare this definition to that of the standard model-based definition
of an anomaly.
(b) For what sizes of data sets (small, medium, or large) is this definition
appropriate?
(a) The standard model-based definition labels objects that don’t fit the
model very well as anomalies. Although these object often are unusu-
ally influential in the model, it can also be the case that an unusually
influential object can fit the model very well.
The standard model-based definition labels objects that don’t fit the
model very well as anomalies. Although these object often are unusu-
ally influential in the model, it can also be the case that an unusually
influential object can fit the model very well.
(b) This definition is typically more appropriate for smaller data sets, at
least if we are talking about one very influential object. However, a
relatively small group highly influential objects can have a significant
impact on a model, but still fit it well, even for medium or large data
sets.
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