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Objects with multiple numeric attributes can be compared within any “subspace” (subset of attributes). In applications such as computational journalism, users are interested i...
You Wu, Pankaj K. Agarwal, Chengkai Li, Jun Yang 0...
This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-rela...
Michael Davis, Weiru Liu, Paul Miller, George Redp...
Nowadays, graph-based knowledge discovery algorithms do not consider numeric attributes (they are discarded in the preprocessing step, or they are treated as alphanumeric values w...
Oscar E. Romero, Jesus A. Gonzalez, Lawrence B. Ho...
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
AODE (Aggregating One-Dependence Estimators) is considered one of the most interesting representatives of the Bayesian classifiers, taking into account not only the low error rate...
?Mining association rules on large data sets has received considerable attention in recent years. Association rules are useful for determining correlations between attributes of a ...