| Analysis of complexity indices for classification problems: Cancer gene expression data | 14 | 0.66 | 2012 |
| Comparing machine learning classifiers in potential distribution modelling | 10 | 0.48 | 2011 |
| On the Complexity of Gene Marker Selection | 2 | 0.38 | 2010 |
| Using Supervised Complexity Measures in the Analysis of Cancer Gene Expression Data Sets | 3 | 0.41 | 2009 |
| Top-Down Hierarchical Ensembles of Classifiers for Predicting G-Protein-Coupled-Receptor Functions | 15 | 0.66 | 2008 |
| On the Complexity of Gene Expression Classification Data Sets | 6 | 0.50 | 2008 |
| Evaluation of Models for the Recognition of Hadwritten Digits in Medical Forms | 0 | 0.34 | 2008 |
| Ensembles of pre-processing techniques for noise detection in gene expression data | 4 | 0.43 | 2008 |
| Potential Distribution Modelling Using Machine Learning | 1 | 0.38 | 2008 |
| Comparing several approaches for hierarchical classification of proteins with decision trees | 15 | 0.70 | 2007 |
| Comparing Several Evaluation Functions in the Evolutionary Design of Multiclass Support Vector Machines | 0 | 0.34 | 2007 |
| Evolutionary design of multiclass support vector machines | 14 | 0.72 | 2007 |
| Support Vector Machines Applied to White Blood Cell Recognition | 9 | 0.90 | 2005 |
| The Influence of Noisy Patterns in the Performance of Learning Methods in the Splice Junction Recognition Problem | 1 | 0.37 | 2002 |
