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GI
2004
Springer

Outlier Detection by Rareness Assumption

13 years 10 months ago
Outlier Detection by Rareness Assumption
: A concept for identification of candidates for outliers is presented, with a focus on nominal variables. The database concerned is searched for rules that are almost universally valid, with rare exceptions. In statistical terms, for these rules, the hypothesis that the rule is universally valid except for random faults cannot be rejected. Outlier candidates are those values that violate these rules.
Tomas Hrycej, Jochen Hipp
Added 01 Jul 2010
Updated 01 Jul 2010
Type Conference
Year 2004
Where GI
Authors Tomas Hrycej, Jochen Hipp
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