FIRE-DES++: Enhanced Online Pruning of Base Classifiers for Dynamic Ensemble Selection

1 October 2018

Papers citing "FIRE-DES++: Enhanced Online Pruning of Base Classifiers for Dynamic Ensemble Selection"

7 / 7 papers shown

Title
Analyzing different prototype selection techniques for dynamic classifier and ensemble selection Rafael M. O. Cruz R. Sabourin George D. C. Cavalcanti 24 20 0 01 Nov 2018
A Method For Dynamic Ensemble Selection Based on a Filter and an Adaptive Distance to Improve the Quality of the Regions of Competence Rafael M. O. Cruz George D. C. Cavalcanti Ing Ren Tsang 20 29 0 01 Nov 2018
META-DES.Oracle: Meta-learning and feature selection for ensemble selection Rafael M. O. Cruz R. Sabourin George D. C. Cavalcanti 28 86 0 01 Nov 2018
META-DES: A Dynamic Ensemble Selection Framework using Meta-Learning Rafael M. O. Cruz R. Sabourin George D. C. Cavalcanti Ing Ren Tsang 40 240 0 30 Sep 2018
DESlib: A Dynamic ensemble selection library in Python Rafael M. O. Cruz L. G. Hafemann R. Sabourin George D. C. Cavalcanti 43 87 0 14 Feb 2018
Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning G. Lemaître Fernando Nogueira Christos K. Aridas 73 2,063 0 21 Sep 2016
Should we really use post-hoc tests based on mean-ranks? A. Benavoli Giorgio Corani Francesca Mangili 46 374 0 09 May 2015