A number of Inductive Logic Programming (ILP) systems have addressed the problem of learning First Order Logic (FOL) discriminant definitions by first reformulating the FOL lear...
Decision tree-based probability estimation has received great attention because accurate probability estimation can possibly improve classification accuracy and probability-based r...
Weintroduce a significant improvementfor a relatively newmachine learning methodcalled Transformation-Based Learning. By applying a MonteCarlo strategy to randomly sample from the...
Symbolic data analysis aims at generalizing some standard statistical data mining methods, such as those developed for classification tasks, to the case of symbolic objects (SOs). ...
Semi-naive Bayesian classifiers seek to retain the numerous strengths of naive Bayes while reducing error by weakening the attribute independence assumption. Backwards Sequential ...