Now showing items 1-3 of 3
Univariate decision tree induction using maximum margin classification
(OXFORD UNIV PRESS, 2012-03)
In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we propose a new decision tree learning algorithm called univariate margin ...
Design and analysis of classifier learning experiments in bioinformatics: survey and case studies
(IEEE COMPUTER SOC, 2012-12)
In many bioinformatics applications, it is important to assess and compare the performances of algorithms trained from data, to be able to draw conclusions unaffected by chance and are therefore significant. Both the design ...
Cost-conscious comparison of supervised learning algorithms over multiple data sets
(ELSEVIER SCI LTD, 2012-04)
In the literature, there exist statistical tests to compare supervised learning algorithms on multiple data sets in terms of accuracy but they do not always generate an ordering. We propose Multi(2)Test, a generalization ...