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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
Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images
(MDPI, 2021)
The morphology of nanoparticles governs their properties for a range of important applica tions. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate ...
Artículo
Asynchronous dual-pipeline deep learning framework for online data stream classification
(IOS Press, 2020)
Data streaming classification has become an essential task in many fields where real-time decisions have to be made based on incoming information. Neural networks are a particularly suitable technique for the streaming ...
Artículo
Data Science and Big Data in Energy Forecasting
(MDPI, 2018-11)
This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal. The special issue took place in 2017 and accepted a ...
Artículo
A data mining based clinical decision support system for survival in lung cancer
(Via Médica Journals, 2021)
Background: A clinical decision support system (CDSS) has been designed to predict the outcome (overall survival) by extracting and analyzing information from routine clinical activity as a complement to clinical guidelines ...
Artículo
External clustering validity index based on chi-squared statistical test
(Elsevier, 2019)
Clustering is one of the most commonly used techniques in data mining. Its main goal is to group objects into clusters so that each group contains objects that are more similar to each other than to objects in other ...
Artículo
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
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
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, ...
Artículo
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 ...