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Artículo
Método de inducción de reglas de clasificación oblicuas mediante un algoritmo evolutivo
(Universidad Autónoma de Bucaramanga, 2002-06-01)
En este artículo presentamos un nuevo método, de nominado OBLIC, para inducción de reglas de clasificación oblicuas no jerárquicas a partir de un conjunto de datos etiquetados. La base del método es un algoritmo evolutivo ...
Artículo
Semi-wrapper feature subset selector for feed-forward neural networks: Applications to binary and multi-class classification problems
(ScienceDirect, 2019-08-11)
This paper explores widely the data preparation stage within the process of knowledge discovery and data mining via feature subset selection in the context of two very well-known neural models: radial basis function neural ...
Artículo
Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance
(Elsevier, 2021)
Object detection has been one of the most active topics in computer vision for the past years. Recent works have mainly focused on pushing the state-of-the-art in the general-purpose COCO benchmark. However, the use of ...
Artículo
Applications of Computational Intelligence in Time Series
(Hindawi, 2017)
Artículo
Energy Time Series Forecasting Based on Pattern Sequence Similarity
(IEEE, 2011)
This paper presents a new approach to forecast the behavior of time series based on similarity of pattern sequences. First, clustering techniques are used with the aim of grouping and labeling the samples from a data set. ...
Artículo
Data Set Editing by Ordered Projection
(IOS Press, 2001)
This paper presents a new approach to data set editing. The algorithm (EOP: Editing by Ordered Projection) has some interesting characteristics: important reduction of the number of examples from the database; lower ...
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
Machine learning techniques to discover genes with potential prognosis role in Alzheimer’s disease using different biological sources
(Elsevier, 2017)
Alzheimer’s disease is a complex progressive neurodegenerative brain disorder, being its prevalence ex pected to rise over the next decades. Unconventional strategies for elucidating the genetic mechanisms are necessary ...
Artículo
Discovering gene association networks by multi-objective evolutionary quantitative association rules
(Elsevier, 2014)
In the last decade, the interest in microarray technology has exponentially increased due to its ability to monitor the expression of thousands of genes simultaneously. The reconstruction of gene association networks ...