Before applying learning algorithms to datasets, practitioners often globally discretize any numeric attributes. If the algorithm cannot handle numeric attributes directly, prior ...
: Research on a new system implementing the AQ learning methodology, called AQ20, is briefly described, and illustrated by initial results from an experimental version. Like its pr...
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
We describe the use of machine learning and data mining to detect and classify malicious executables as they appear in the wild. We gathered 1,971 benign and 1,651 malicious execu...
We describe techniques for combining two types of knowledge systems: expert and machine learning. Both the expert system and the learning system represent information by logical d...