Listar por autor UPNA "Sanz Delgado, José Antonio"
Mostrando ítems 1-20 de 33
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Aggregation and pre-aggregation functions in fuzzy rule-based classification systems
Una manera eficiente de tratar problemas de clasificación, entre otras, es el uso de Sistemas de Clasificación Basados en Reglas Difusas (SCBRDs). Estos sistemas están compuestos por dos componentes principales, la Base ... -
Aggregation functions to combine RGB color channels in stereo matching
In this paper we present a comparison study between different aggregation functions for the combination of RGB color channels in stereo matching problem. We introduce color information from images to the stereo matching ... -
Automatic detection of high-voltage power lines in LiDAR surveys using data mining techniques
The correct classification of power lines in LiDAR point clouds has attracted the interest of the mapping community in the last years. The objective of this research is the detection and automatic extraction of high-voltage ... -
CFM-BD: a distributed rule induction algorithm for building compact fuzzy models in Big Data classification problems
Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions and decisions. However, when it comes to ... -
A compact evolutionary interval-valued fuzzy rule-based classification system for the modeling and prediction of real-world financial applications with imbalanced data
The current financial crisis has stressed the need of obtaining more accurate prediction models in order to decrease the risk when investing money on economic opportunities. In addition, the transparency of the process ... -
Construction of capacities from overlap indexes
In this chapter, we show how the concepts of overlap function and overlap index can be used to define fuzzy measures which depend on the specific data of each considered problem. -
dCF-integrals: generalizing CF-integrals by means of restricted dissimilarity functions
The Choquet integral (CI) is an averaging aggregation function that has been used, e.g., in the fuzzy reasoning method (FRM) of fuzzy rule-based classification systems (FRBCSs) and in multicriteria decision making in order ... -
A decision tree based approach with sampling techniques to predict the survival status of poly-trauma patients
Survival prediction of poly-trauma patients measure the quality of emergency services by comparing their predictions with the real outcomes. The aim of this paper is to tackle this problem applying C4.5 since it achieves ... -
Enhancing multi-class classification in FARC-HD fuzzy classifier: on the synergy between n-dimensional overlap functions and decomposition strategies
There are many real-world classification problems involving multiple classes, e.g., in bioinformatics, computer vision or medicine. These problems are generally more difficult than their binary counterparts. In this scenario, ... -
Enhancing the efficiency of the interval-valued fuzzy rule-based classifier with tuning and rule selection
Interval-Valued fuzzy rule-based classifier with TUning and Rule Selection, IVTURS, is a state-of-the-art fuzzy classifier. One of the key point of this method is the usage of interval-valued restricted equivalence functions ... -
Evolution in time of L-fuzzy context sequences
In this work, we consider a complete lattice L and we study L-fuzzy context sequences which represent the evolution in time of an L-fuzzy context. To carry out this study, in the first part of the paper, we consider n-ary ... -
An evolutionary underbagging approach to tackle the survival prediction of trauma patients: a case study at the Hospital of Navarre
Survival prediction systems are used among emergency services at hospitals in order to measure their quality objectively. In order to do so, the estimated mortality rate given by a prediction model is compared with the ... -
Extensions of fuzzy sets in image processing: an overview
This work presents a valuable review for the interested reader of the recent Works using extensions of fuzzy sets in image processing. The chapter is divided as follows: first we recall the basics of the extensions of fuzzy ... -
A first study on the use of interval-valued fuzzy sets with genetic tuning for classification with imbalanced data sets
Classification with imbalanced data-sets is one of the recent challenging problems in Data Mining. In this framework, the class dis- tribution is not uniform and the separability between the classes is often difficult. ... -
A fuzzy association rule-based classifier for imbalanced classification problems
Imbalanced classification problems are attracting the attention of the research community because they are prevalent in real-world problems and they impose extra difficulties for learning methods. Fuzzy rule-based ... -
Fuzzy rule-based classification systems for multi-class problems using binary decomposition strategies: on the influence of n-dimensional overlap functions in the fuzzy reasoning method
Multi-class classification problems appear in a broad variety of real-world problems, e.g., medicine, genomics, bioinformatics, or computer vision. In this context, decomposition strategies are useful to increase the ... -
General admissibly ordered interval-valued overlap functions
(CEUR Workshop Proceedings (CEUR-WS.org), 2021) Contribución a congreso / Biltzarrerako ekarpenaOverlap functions are a class of aggregation functions that measure the verlapping degree between two values. They have been successfully applied in several problems in which associativity is not required, such as ... -
General grouping functions
Some aggregation functions that are not necessarily associative, namely overlap and grouping functions, have called the attention of many researchers in the recent past. This is probably due to the fact that they are a ... -
A genetic tuning to improve the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets: degree of ignorance and lateral position
Fuzzy Rule-Based Systems are appropriate tools to deal with classification problems due to their good properties. However, they can suffer a lack of system accuracy as a result of the uncertainty inherent in the definition ... -
IIVFDT: ignorance functions based interval-valued fuzzy decision tree with genetic tuning
The choice of membership functions plays an essential role in the success of fuzzy systems. This is a complex problem due to the possible lack of knowledge when assigning punctual values as membership degrees. To face this ...