<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Long-Short Term Memory for Time-Series Forecasting, Enhanced</dc:title>
  <dc:title>R package TSLSTMplus version 1.0.6</dc:title>
  <dc:subject>CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries)</dc:subject>
  <dc:description>The LSTM (Long Short-Term Memory) model is a Recurrent Neural Network (RNN) based architecture that is widely used for time series forecasting. Customizable configurations for the model are allowed, improving the capabilities and usability of this model compared to other packages. This package is based on 'keras' and 'tensorflow' modules and the algorithm of Paul and Garai (2021) &lt;doi:10.1007/s00500-021-06087-4&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Imports: keras, tensorflow, stats, abind</dc:relation>
  <dc:creator>Jaime Pizarroso Gonzalo &lt;jpizarroso@comillas.edu&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Jaime Pizarroso Gonzalo [aut, ctb, cre],
  Antonio Muñoz San Roque [aut]</dc:contributor>
  <dc:rights>GPL-3</dc:rights>
  <dc:date>2025-02-03</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=TSLSTMplus</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.TSLSTMplus</dc:identifier>
</oai_dc:dc>