4 citations · 6 across the 8 of their papers we have counts for
9 papers
The Matthews Correlation Coefficient: Fifty years
Jesus S. Aguilar-Ruiz
Fifty years after its introduction, the Matthews Correlation Coefficient (MCC) remains central -and debated- in binary classification. This survey offers a comprehensive retrospect…
When to Truncate a Feature Ranking: A Residual-Overlap Stopping Rule for Subset Selection
Jesus S. Aguilar-Ruiz
Feature rankings are widely used in supervised feature selection because they are simple, scalable and easy to interpret. Variables are first ranked by a relevance score, and a sub…
Irredundant -Fold Cross-Validation
Jesus S. Aguilar-Ruiz
In traditional k-fold cross-validation, each instance is used () times for training and once for testing, leading to redundancy that lets many instances disproportionately inf…
Rethinking Review Citations: Impact on Scientific Integrity
Jesus S. Aguilar-Ruiz
The proliferation of surveys and review articles in academic journals has impacted citation metrics like impact factor and h-index, skewing evaluations of journal and researcher qu…
The Certainty Ratio : a novel metric for assessing the reliability of classifier predictions
Jesus S. Aguilar-Ruiz
Evaluating the performance of classifiers is critical in machine learning, particularly in high-stakes applications where the reliability of predictions can significantly impact de…
Class-specific feature selection for classification explainability
Jesus S. Aguilar-Ruiz
Feature Selection techniques aim at finding a relevant subset of features that perform equally or better than the original set of features at explaining the behavior of data. Typic…
XNB: Explainable Class-Specific NaIve-Bayes Classifier
Jesus S. Aguilar-Ruiz, Cayetano Romero, Andrea Cicconardi
In today's data-intensive landscape, where high-dimensional datasets are increasingly common, reducing the number of input features is essential to prevent overfitting and improve…
Land use identification through social network interaction
Diana C. Pauca-Quispe, Cinthya Butron-Revilla, Ernesto Suarez-Lopez +2
The Internet generates large volumes of data at a high rate, in particular, posts on social networks. Although social network data has numerous semantic adulterations, and is not i…
Boolean Reasoning-Based Biclustering for Shifting Pattern Extraction
Marcin Michalak, Jesús S. Aguilar-Ruiz
Biclustering is a powerful approach to search for patterns in data, as it can be driven by a function that measures the quality of diverse types of patterns of interest. However, d…