Listar por tema "Ensembles"
Mostrando ítems 1-9 de 9
-
Desarrollo de un mecanismo de combinación de clasificadores basado en los vectores de salidas más cercanas
Este proyecto consiste en desarrollar un nuevo modelo de combinación de clasificadores basado en la similitud entre las salidas que se obtienen entre el ejemplo a clasificar y los ejemplos de entrenamiento. Es decir, ... -
An empirical study on supervised and unsupervised fuzzy measure construction methods in highly imbalanced classification
The design of an ensemble of classifiers involves the definition of an aggregation mechanism that produces a single response obtained from the information provided by the classifiers. A specific aggregation methodology ... -
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 ... -
INFFC: an iterative class noise filter based on the fusion of classifiers with noise sensitivity control
In classification, noise may deteriorate the system performance and increase the complexity of the models built. In order to mitigate its consequences, several approaches have been proposed in the literature. Among them, ... -
Mejora de los algoritmos de minería de datos: combinación de clasificadores, preprocesamiento y sus aplicaciones
El objetivo general de esta tesis es tratar de mejorar los resultados que se obtienen en los problemas de clasificación mejorando las fases que preceden y suceden a la fase de aprendizaje, es decir, a la construcción del ... -
A supervised fuzzy measure learning algorithm for combining classifiers
(Elsevier, 2023) Artículo / ArtikuluaFuzzy measure-based aggregations allow taking interactions among coalitions of the input sources into account. Their main drawback when applying them in real-world problems, such as combining classifier ensembles, is how ... -
A survey of fingerprint classification Part I: taxonomies on feature extraction methods and learning models
This paper reviews the fingerprint classification literature looking at the problem from a double perspective. We first deal with feature extraction methods, including the different models considered for singular point ... -
A survey of fingerprint classification Part II: experimental analysis and ensemble proposal
In the first part of this paper we reviewed the fingerprint classification literature from two different perspectives: the feature extraction and the classifier learning. Aiming at answering the question of which among the ... -
Unsupervised fuzzy measure learning for classifier ensembles from coalitions performance
In Machine Learning an ensemble refers to the combination of several classifiers with the objective of improving the performance of every one of its counterparts. To design an ensemble two main aspects must be considered: ...