16 citations · 44 across the 7 of their papers we have counts for
7 papers
Semi-Supervised Constrained Clustering: An In-Depth Overview, Ranked Taxonomy and Future Research Directions
Germán González-Almagro, Daniel Peralta, Eli De Poorter +2
Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering…
Predict+Optimize Problem in Renewable Energy Scheduling
Christoph Bergmeir, Frits de Nijs, Evgenii Genov +25
Predict+Optimize frameworks integrate forecasting and optimization to address real-world challenges such as renewable energy scheduling, where variability and uncertainty are criti…
Polar Encoding: A Simple Baseline Approach for Classification with Missing Values
Oliver Urs Lenz, Daniel Peralta, Chris Cornelis
We propose polar encoding, a representation of categorical and numerical -valued attributes with missing values to be used in a classification context. We argue that this is…
No imputation without representation
Oliver Urs Lenz, Daniel Peralta, Chris Cornelis
By filling in missing values in datasets, imputation allows these datasets to be used with algorithms that cannot handle missing values by themselves. However, missing values may i…
Optimised one-class classification performance
Oliver Urs Lenz, Daniel Peralta, Chris Cornelis
We provide a thorough treatment of one-class classification with hyperparameter optimisation for five data descriptors: Support Vector Machine (SVM), Nearest Neighbour Distance (NN…
Average Localised Proximity: A new data descriptor with good default one-class classification performance
Oliver Urs Lenz, Daniel Peralta, Chris Cornelis
One-class classification is a challenging subfield of machine learning in which so-called data descriptors are used to predict membership of a class based solely on positive exampl…
On the use of convolutional neural networks for robust classification of multiple fingerprint captures
Daniel Peralta, Isaac Triguero, Salvador García +3
Fingerprint classification is one of the most common approaches to accelerate the identification in large databases of fingerprints. Fingerprints are grouped into disjoint classes,…