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...
Discretization algorithms have played an important role in data mining and knowledge discovery. They not only produce a concise summarization of continuous attributes to help the ...
Discrete values have important roles in data mining and knowledge discovery. They are about intervals of numbers which are more concise to represent and specify, easier to use and ...
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...