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Predicción de módulos defectuosos como un problema de optimización multiobjetivo
(Asociación de Ingeniería del Software y Tecnologías de Desarrollo de Software (SISTEDES), 2017)
La dificultad de aplicar técnicas de análisis de datos al problema de la calidad del software radica principalmente en dos razones: la ausencia de datos generalistas y de herramientas específicas. En este trabajo exponemos ...
Artículo
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An approach to validity indices for clustering techniques in Big Data
(Springer, 2018)
Clustering analysis is one of the most used Machine Learning techniques to discover groups among data objects. Some clustering methods require the number of clus ters into which the data is going to be partitioned. There ...
Artículo
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MOMIC: A multi-omics pipeline for data analysis, integration and interpretation
(MDPI, 2022)
Background and Objectives: The burst of high-throughput omics technologies has given rise to a new era in systems biology, offering an unprecedented scenario for deriving meaningful biological knowledge through the ...
Artículo
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Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model
(Mary Ann Liebert, 2020)
This study proposes a novel bioinspired metaheuristic simulating how the coronavirus spreads and infects healthy people. From a primary infected individual (patient zero), the coronavirus rapidly infects new victims, ...
Ponencia
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A preliminary study on deep transfer learning applied to image classification for small datasets
(Springer, 2020)
A new transfer learning strategy is proposed for image classification in this work, based on an 8-layer convolutional neural network. The transfer learning process consists in a training phase of the neural network on a ...
Ponencia
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SmartFD: A Real Big Data Application for Electrical Fraud Detection
(Springer, 2018)
The main objective of this paper is the application of big data analytics to a real case in the field of smart electric networks. Smart meters are not only elements to measure consumption, but they also con stitute a ...
Artículo
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Recent Advances in Energy Time Series Forecasting
(MDPI, 2017)
This editorial summarizes the performance of the special issue entitled Energy Time Series Forecasting, which was published in MDPI’s Energies journal. The special issue took place in 2016 and accepted a total of 21 ...
Ponencia
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Aproximación al índice externo de validación de clustering basado en chi cuadrado
(Asociación Española para la Inteligencia Artificial (AEPIA), 2018)
El clustering es una de las técnicas más utilizadas en minería de datos. Tiene como objetivo principal agrupar datos en clusters de manera que los objetos que pertenecen al mismo clúster sean más similares que los que ...
Ponencia
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An Approach to Silhouette and Dunn Clustering Indices Applied to Big Data in Spark
(Springer, 2016)
K-Means and Bisecting K-Means clustering algorithms need the optimal number into which the dataset may be divided. Spark implementations of these algorithms include a method that is used to calculate this number. Unfortunately, ...
Ponencia
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On the performance of deep learning models for time series classification in streaming
(Springer, 2020)
Processing data streams arriving at high speed requires the development of models that can provide fast and accurate predictions. Although deep neural networks are the state-of-the-art for many machine learning tasks, ...