Most rule learning systems posit hard decision boundaries for continuous attributes and point estimates of rule accuracy, with no measures of variance, which may seem arbitrary to ...
Lemuel R. Waitman, Douglas H. Fisher, Paul H. King
Analyzing data to find trends, correlations, and stable patterns is an important problem for many industrial applications. In this paper, we propose a new technique based on paral...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead ...
Given a set of rating data for a set of items, determining the values of items is a matter of importance and various probability models have been proposed. The Plackett-Luce model ...
Satisfying the basic requirements of accuracy and understandability of a classifier, decision tree classifiers have become very popular. Instead of constructing the decision tree ...
Mihael Ankerst, Christian Elsen, Martin Ester, Han...