Experimental analysis of the performance of a proposed method is a crucial and necessary
task in an investigation. In this paper, we focus on the use of nonparametric statistical …

In the paper we present some guidelines for the application of nonparametric statistical tests
and post-hoc procedures devised to perform multiple comparisons of machine learning …

In a recently published paper in JMLR, Demšar (2006) recommends a set of non-parametric
statistical tests and procedures which can be safely used for comparing the performance of …

In this paper, we focus on the experimental analysis on the performance in artificial neural
networks with the use of statistical tests on the classification task. Particularly, we have …

In social sciences, education, and public health research, researchers often conduct small
pilot studies (or may have planned for a larger sample but lost too many cases due to …

While methods for comparing two learning algorithms on a single data set have been
scrutinized for quite some time already, the issue of statistical tests for comparisons of more …

While there are books focusing on parametric tests, the domain of nonparametric tests is
mostly unexplored. Data Analysis in Business Research: A Step by Step Nonparametric …

The statistical comparison of multiple algorithms over multiple data sets is fundamental in
machine learning. This is typically carried out by the Friedman test. When the Friedman test …

The assessment of the performance of learners by means of benchmark experiments is an
established exercise. In practice, benchmark studies are a tool to compare the performance …

This work is builds on the study of the 10 top data mining algorithms identified by the IEEE
International Conference on Data Mining (ICDM) community in December 2006. We address …