On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms

20 March 2017

Papers citing "On the Use of Default Parameter Settings in the Empirical Evaluation of Classification Algorithms"

4 / 4 papers shown

Title
Handling Imbalanced Classification Problems With Support Vector Machines via Evolutionary Bilevel Optimization Alejandro Rosales-Pérez S. García Francisco Herrera 76 17 0 21 Apr 2022
AutonoML: Towards an Integrated Framework for Autonomous Machine Learning D. Kedziora Katarzyna Musial Bogdan Gabrys 94 17 0 23 Dec 2020
Enhancing Selection Hyper-heuristics via Feature Transformations I. Amaya J. C. Ortíz-Bayliss Alejandro Rosales-Pérez A. E. Gutiérrez-Rodríguez S. E. Conant-Pablos Hugo Terashima-Marín C. Coello 30 19 0 12 Dec 2018
The Heterogeneous Ensembles of Standard Classification Algorithms (HESCA): the Whole is Greater than the Sum of its Parts J. Large Jason Lines A. Bagnall 58 28 0 25 Oct 2017