Know Your Data: Part 2

Noise

Many says if there is no noise in data, data mining would be too easy. Noise in data represent the modification of original values. Prof Jeff M. Phillips from University of Utah defines the main causes of noise in data as mentioned below.

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Outliers

As the name implies, outliers are data objects which are considerably different than most of the other data objects. The object pointed in below image has different (X,Y) attributes than all other data objects hence qualifies for outlier.

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Missing values

It is very much possible to have data objects with missing one or multiple attribute values.

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Duplicate data

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Full Text： kdnuggets

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