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Implementing the Cumulative Difference Plot in the IOHanalyzer
Arza, E.
; Ceberio, J.; Irurozki, E.; Pérez, A. (2022-07)
; Ceberio, J.; Irurozki, E.; Pérez, A. (2022-07)
The IOHanalyzer is a web-based framework that enables an easy visualization and comparison of the quality of stochastic optimization algorithms. IOHanalyzer offers several graphical and statistical tools analyze the results ...
Generalized Maximum Entropy for Supervised Classification
Mazuelas, S.; Shen, Y.; Pérez, A. (2022-04)
; Shen, Y.; Pérez, A. (2022-04)
The maximum entropy principle advocates to
evaluate events’ probabilities using a distribution that maximizes
entropy among those that satisfy certain expectations’ constraints. Such principle can be generalized for ...
Time Series Classifier Recommendation by a Meta-Learning Approach
Abanda, A.; Mori, U.; Lozano, J.A. (2022-03-26)
; Mori, U.; Lozano, J.A. (2022-03-26)
This work addresses time series classifier recommendation for the first time in the literature by considering several recommendation forms or meta-targets: classifier accuracies, complete ranking, top-M ranking, best set ...
Modeling latent spatio-temporal disease incidence using penalized composite link models
Lee, D.-J.; Durban, M.; Ayma, D.; Van de Kassteele, J. (2022-03-10)
; Durban, M.; Ayma, D.; Van de Kassteele, J. (2022-03-10)
Epidemiological data are frequently recorded at coarse spatio-temporal resolutions to protect confidential information or to summarize it in a compact manner. However, the detailed patterns followed by the source data, ...
Preference incorporation into many-objective optimization: An Ant colony algorithm based on interval outranking
Rivera, G.; Coello, C.A.; Cruz-Reyes, L.; Fernandez, E.R.; Gomez-Santillan, C.; Rangel-Valdez, N. (2022-03-01)
; Cruz-Reyes, L.; Fernandez, E.R.; Gomez-Santillan, C.; Rangel-Valdez, N. (2022-03-01)
In this paper, we enriched Ant Colony Optimization (ACO) with interval outranking to develop a novel multi-objective ACO optimizer to approach problems with many objective functions. This proposal is suitable if the ...
EDA++: Estimation of Distribution Algorithms with Feasibility Conserving Mechanisms for Constrained Continuous Optimization
Shirazi, A.; Ceberio, J.; Lozano, J.A. (2022-02-25)
; Ceberio, J.; Lozano, J.A. (2022-02-25)
Handling non-linear constraints in continuous optimization is challenging, and finding a feasible solution is usually a difficult task. In the past few decades, various techniques have been developed to deal with linear ...
A two-stage approach for the spatio-temporal analysis of high-throughput phenotyping data
Pérez, D.M.; Rodríguez-Álvarez, M.X.; Boer, M.P; Kronenberg, L.; Hund, A.; Cabrera-Bosquet, L.; Millet, E.J.; van Eeuwijk, F.A. (2022-02-24)
; Rodríguez-Álvarez, M.X.; Boer, M.P; Kronenberg, L.; Hund, A.; Cabrera-Bosquet, L.; Millet, E.J.; van Eeuwijk, F.A. (2022-02-24)
High throughput phenotyping (HTP) platforms and devices are increasingly used for the characterization of growth and developmental processes for large sets of plant genotypes. Such HTP data require challenging statistical ...
A Deep Learning Approach for Generating Soft Range Information from RF Data
li, Y.; Mazuelas, S.; Shen, Y. (2022-01-24)
; Shen, Y. (2022-01-24)
Radio frequency (RF)-based techniques are widely
adopted for indoor localization despite the challenges in extracting
sufficient information from measurements. Soft range
information (SRI) offers a promising alternative ...
Derivation of a Cost-Sensitive COVID-19 Mortality Risk Indicator Using a Multistart Framework
Armañanzas, R.; Diaz, A.; Martinez, M.; Mazuelas, S. (2022-01-14)
; Diaz, A.; Martinez, M.; Mazuelas, S. (2022-01-14)
The overall global death rate for COVID-19 patients
has escalated to 2.13% after more than a year of worldwide
spread. Despite strong research on the infection pathogenesis, the
molecular mechanisms involved in a fatal ...
A Multivariate Time Series Streaming Classifier for Predicting Hard Drive Failures [Application Notes]
Ircio, J.; Lojo, A.; Mori, U.; Lozano, J.A. (2022)
(2022)
Digital data storage systems such as hard drives can suffer breakdowns that cause the loss of stored data. Due to the cost of data and the damage that its loss entails, hard drive failure prediction is vital. In this ...