Person:
Gómez González, Daniel

First Name

Daniel

Last Name

Gómez González

URI

https://hdl.handle.net/20.500.14352/77430

Affiliation

Universidad Complutense de Madrid

Faculty / Institute

Estudios estadísticos

Department

Estadística y Ciencia de los Datos

Area

Estadística e Investigación Operativa

Identifiers

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Now showing 1 - 10 of 28

Project number: 177
Utilización de metodologías activas de enseñanza para el aprendizaje de las matemáticas, centradas en el estudiante y desarrolladas en el espacio innovador de una hiperaula
(2021) Fernández-Salinero Miguel, Carolina; Riva Picatoste, Beatriz De la; Roanes Lozano, Eugenio; Roanes Macías, Eugenio; Gómez González, Daniel; Muñoz Fernández, Gustavo Adolfo; Lucas Burgos, Daniel; Flores Vidal, Pablo Arcadio; Giorgis, Valentina; Sáez Maestro, Eva
La inauguración de la hiperaula de la Facultad de Educación-CFP (UCM) en abril de 2019 y su prioridad de uso para el Máster en Formación del Profesorado de Educación Secundaria, Bachillerato, Formación Profesional y Enseñanza de Idiomas durante el curso académico 2019-2020, supone un marco experimental absolutamente novedoso. Estas circunstancias permiten a la responsable del proyecto y a varios profesores participantes en el mismo, algunos de ellos docentes en el mencionado Máster y pertenecientes a diferentes Departamentos y Facultades de la UCM, así como a varios alumni y personal de administración y servicios implicados en el proyecto, utilizar este innovador espacio para la enseñanza de la asignatura de "Innovación docente e iniciación a la investigación educativa" (especialidad de matemáticas del Máster en Formación del Profesorado), empleando para ello metodologías activas de enseñanza centradas en el estudiante.
On measuring features importance in Machine Learning models in a two-dimensional representation scenario
(2022) Gutiérrez García-Pardo, Inmaculada; Santos, Daniel; Castro Cantalejo, Javier; Gómez González, Daniel; Espínola Vílchez, María Rosario; Guevara Gil, Juan Antonio
Abstract: There is a wide range of papers in the literature about the explanation of machine learning models in which Shapley value is considered to measure the importance of the features in these models. We can distinguish between these which set their basis on the cooperative game theory principles, and these focused on fuzzy measures. It is important to mention that all of these approaches only provide a crisp value (or a fix point) to measure the importance of a feature in a specific model. The reason is that an aggregation process of the different marginal contributions produces a single output for each variable. Nevertheless, and because of the relations between features, we cannot distinguish the case in which we do not know all the features. To this aim, we propose a disaggregated model which allows the analysis of the importance of the features, regarding the available information. This new proposal can be viewed as a generalization of all previous measures found in literature providing a two dimensional graph which, in a very intuitive and visual way, provides this rich disaggregated information. This information may be aggregated with several aggregation functions with which obtain new measures to establish the importance of the features. Specifically, the aggregation by the sum results in the Shapley value. We also explain the characteristics of those graphics in different scenarios of the relations among features, to raise this useful information at a glance.
The Un-Connectivity of Connective Parties: Analyzing the Online Interaction Patterns of Unidos Podemos in Spain
(Journal of Political Marketing, 2022) Stefano De Marco; Robles Morales, José Manuel; Borja Moya-Gómez; Gómez González, Daniel; taylor and francis
Connective parties (Bennett, Segerberg, and Knüpfer Citation2018) are supposed to create a new scenario in online political communication. They are conceived as new political subjects, characterized by reciprocal communication flows across social networking sites (SNSs), and the creation of fluid online relationships between “connective representatives” and their constituents. This paper focuses on the Spanish connective party “Podemos” to test this hypothesis, by comparing the communicative styles of Spanish Members of Parliament (MPs) on Twitter, depending on their reference party and the interlocutor they are interacting with. Our results show that Podemos MPs are not more inclined to interact with ordinary citizens than MPs from other political parties, and this provides further evidence against the idea that SNSs could strengthen the relationship between representatives and citizens, at least in the case of Spain. Instead, SNSs appear to be used as tools for the one-way transmission of messages from political parties and representatives, leading to the conclusion that they play an important role in spreading political messages to large audiences and in political campaigning, but not in fostering deliberation.
Allocating slacks in stochastic PERT network
(Central European journal of operations research, 2014) Castro Cantalejo, Javier; Gómez González, Daniel; Tejada Cazorla, Juan Antonio
The SPERT problem was defined, in a game theory framework, as the fair allocation of the slack or float among the activities in a PERT network previous to the execution of the project. Previous approaches tackle with this problem imposing that the durations of the activities are deterministic. In this paper, we extend the SPERT problem into a stochastic framework defining a new solution that tries also to maintain the good performance of some other approaches that have been defined for the deterministic case. Afterward, we present a polynomial algorithm for this new solution that also could be used for the calculation of other approaches founded in the deterministic SPERT literature.
Multiple bipolar fuzzy measures: an application to community detection problems for networks with additional information
(International Journal of Computational Intelligence Systems, 2020) Gutiérrez García-Pardo, Inmaculada; Gómez González, Daniel; Castro Cantalejo, Javier; Espínola Vílchez, María Rosario
In this paper we introduce the concept of multiple bipolar fuzzy measures as a generalization of a bipolar fuzzy measure. We also propose a new definition of a group, which is based on the multidimensional bipolar fuzzy relations of its elements. Taking into account this information, we provide a novel procedure (based on the well-known Louvain algorithm) to deal with community detection problems. This new method considers the multidimensional bipolar information provided by multiple bipolar fuzzy measures, as well as the information provided by a graph. We also give some detailed computational tests, obtained from the application of this algorithm in several benchmark models.
Polarization measures in bi-partition networks based on fuzzy graphs
(2022) Simón de Blas, Clara; Guevara Gil, Juan Antonio; Morillo, Jaime; Gómez González, Daniel
Abstract: In this paper we extend the definition of polarization in a network, by defining a new measure in fuzzy graphs. We will focus on the case of two communities in a fuzzy context. We present a well known problem in real life social networks to compare our results with the crisp case. Results shows improvements in detecting polarization masked in a crisp context.
A new edge betweenness measure using a game theoretical approach: an application to hierarchical community cetection
(Mathematics, 2021) Espínola Vílchez, María Rosario; Gómez González, Daniel; Castro Cantalejo, Javier; Gutiérrez García-Pardo, Inmaculada; Jiménez-Losada, Andrés; Goubko, Mikhail
In this paper we formally define the hierarchical clustering network problem (HCNP) as the problem to find a good hierarchical partition of a network. This new problem focuses on the dynamic process of the clustering rather than on the final picture of the clustering process. To address it, we introduce a new hierarchical clustering algorithm in networks, based on a new shortest path betweenness measure. To calculate it, the communication between each pair of nodes is weighed by the importance of the nodes that establish this communication. The weights or importance associated to each pair of nodes are calculated as the Shapley value of a game, named as the linear modularity game. This new measure, (the node-game shortest path betweenness measure), is used to obtain a hierarchical partition of the network by eliminating the link with the highest value. To evaluate the performance of our algorithm, we introduce several criteria that allow us to compare different dendrograms of a network from two point of view: modularity and homogeneity. Finally, we propose a faster algorithm based on a simplification of the node-game shortest path betweenness measure, whose order is quadratic on sparse networks. This fast version is competitive from a computational point of view with other hierarchical fast algorithms, and, in general, it provides better results.
The cohesiveness of subgroups in social networks: a view from game theory
(Annals of Operations Research, 2007) Gómez González, Daniel; González Arangüena, Enrique; Manuel García, Conrado Miguel; Owen, Guillermo; Pozo Juan, Mónica; Saboyá, Martha; Boros, Endre
A family of cohesiveness measures, based on game theoretical concepts, is proposed for subgroups in social networks. Given a communication situation, consisting of a coalitional game and a graph, both defined on the same set of players-nodes, cohesiveness of a subset is defined as the proportion of their worth that the players in subset retain, when the originally deterministic (restricted) graph becomes a probabilistic one (in a specific manner). Conditions on the game are given to reach some desirable properties.
A new approach to Color Edge Detection
(Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), 2019) Flores Vidal, Pablo Arcadio; Gómez González, Daniel; Castro Cantalejo, Javier; Villarino, Guillermo; Montero, Javier
Most edge detection algorithms deal only with grayscale images, and the way of adapting them to use with RGB images is an open problem. In this work, we explore different ways of aggregating the color information of a RGB image for edges extraction, and this is made by means of well-known edge detection algorithms. In this research, it is been used the set of images from Berkeley. In order to evaluate the algorithm’s performance, F measure is computed. The way that color information -the different channels- is aggregated is proved to be relevant for the edge detection task. Moreover, post-aggregation of channels performed significatively better than the classic approach (pre-aggregation of channels).
A unified approach to the Myerson value and the position value
(Theory and Decision, 2004) Gómez González, Daniel; González Arangüena, Enrique; Manuel García, Conrado Miguel; Owen, Guillermo; Pozo Juan, Mónica; Abdellaoui, Mohammed
We reconsider the Myerson value and the position value for communication situations. In case the underlying game is a unanimity game, we show that each of these values can be computed using the inclusion-exclusion principle. Linearity of both values permits us to calculate them without needing the dividends of the induced games (graph-restricted game and link game). The expression of these dividends is only derived in the existing literature for special communication situations. Moreover, the associated inclusion-exclusion decomposability property depends on what we have called the graph allocation rule. This rule is the relative degree (relative indicator) for the position value (Myerson value).