Listar por materia "Machine learning algorithms"
Mostrando publicaciones 1-5 de 5
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A new fast training algorithm for autoencoder neural networks based on extreme learning machine
; Mora, Marco
; ; ; ; (2022)
Autoencoders are neural networks that are characterized by having the same inputs and outputs. This kind of Neural Networks aim to estimate a nonlinear transformation whose parameters allow to represent the input patterns ...
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Analysis of spectrum detection and decision using machine learning algorithms in cognitive mobile radio networks
(2021)In this work, the performance of four Machine Learning Algorithms (MLAs) applied to Cognitive Mobile Radio Networks (CMRNs) are analyzed. These algorithms are Coalition Game Theory (CGT), Naive Bayesian Classifier (NBC), ...
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Extreme learning machine for mass spectrometry data analysis
(2022)In this work, we introduce the use of a weighted extreme learning machine (ELM) to give an automated predictive value to mass spectrometry data. In specific, the data obtained with Matrix-Assisted Laser DesorptioMonization-Time ...
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Metagenomic binning based on unsupervised extreme learning machine
; ; Mora, Marco; Cuadros-Orellana, Sara (2023)
Metagenomics studies the genetic information of microbial communities in different contexts. As metagenomic DNA is often fragmented and then sequenced into small reads, these reads can be assembled into longer sequences ...
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Using the random forest algorithm for searching behavior patterns in electronic health records
(2019)The search for information associated with qualitative data is usually done using data mining algorithms, the presented research analyzes data of patients with essential hypertension (HTA), patients who have developed ...