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Mostrando ítems 11-20 de 87
Artículo
An Experimental Review on Deep Learning Architectures for Time Series Forecasting
(World Scientific, 2021)
In recent years, deep learning techniques have outperformed traditional models in many machine learning tasks. Deep neural networks have successfully been applied to address time series forecasting problems, which is a ...
Artículo
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems
(Elsevier, 2018)
Many algorithms have emerged to address the discovery of quantitative association rules from datasets in the last years. However, this task is becoming a challenge because the processing power of most existing techniques ...
Artículo
Comparing artificial intelligence strategies for early sepsis detection in the ICU: an experimental study
(Springer, 2023)
Sepsis is a life-threatening condition whose early recognition is key to improving outcomes for patients in intensive care units (ICUs). Artificial intelligence can play a crucial role in mining and exploiting health data ...
Artículo
A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks
(MDPI, 2019)
Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques ...
Artículo
Evolutionary association rules for total ozone content modeling from satellite observations
(Elsevier, 2011)
In this paper we propose an evolutionary method of association rules discovery (EQAR, Evolutionary Quan titative Association Rules) that extends a recently published algorithm by the authors and we describe its ap plication ...
Artículo
Searching for rules to detect defective modules: A subgroup discovery approach
(Elsevier, 2012)
Data mining methods in software engineering are becoming increasingly important as they can support several aspects of the software development life-cycle such as quality. In this work, we present a data mining approach ...
Artículo
Minería de Datos: Conceptos y Tendencias
(IBERAMIA : Sociedad Iberoamericana de Inteligencia Artificial, 2006)
Hoy en día, la minería de datos (MD) está consiguiendo cada vez más captar la atención de las empresas. Todavía es infrecuente oír frases como “deberíamos segmentar a nuestros clientes utilizando herramientas de MD”, “la ...
Artículo
Knowledge-Based Fast Evaluation for Evolutionary Learning
(IEEE, 2005)
The increasing amount of information available is encouraging the search for efficient techniques to improve the data mining methods, especially those which consume great computational resources, such as evolutionary ...
Artículo
Evolutionary feature selection to estimate forest stand variablesusing LiDAR
(Elsevier, 2014)
Light detection and ranging (LiDAR) has become an important tool in forestry. LiDAR-derived models are mostly developed by means of multiple linear regression (MLR) after stepwise selection of predictors. An increasing ...
Artículo
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets
(iOS Press, 2015)
Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes in a subspace of instances from datasets. Genetic algorithms have been extensively used to find ...