J Liu, Y Xu - International Journal of Computational Intelligence …, 2022 - Springer
To prove that a certain algorithm is superior to the benchmark algorithms, the statistical hypothesis tests are commonly adopted with experimental results on a number of datasets …
B Trawiński, M Smętek, Z Telec, T Lasota - International Journal of …, 2012 - sciendo.com
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 …
S Garcia, F Herrera - Journal of machine learning research, 2008 - jmlr.org
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 …
This book provides a modern and accessible overview of computationally intensive nonparametric statistical methods. It presents detailed information on the use of permutation …
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 …
J Demšar - The Journal of Machine learning research, 2006 - jmlr.org
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 …
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 …