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TSLSTMplus  

Long-Short Term Memory for Time-Series Forecasting, Enhanced
View on CRAN: Click here


Download and install TSLSTMplus package within the R console
Install from CRAN:
install.packages("TSLSTMplus")

Install from Github:
library("remotes")
install_github("cran/TSLSTMplus")

Install by package version:
library("remotes")
install_version("TSLSTMplus", "1.0.5")



Attach the package and use:
library("TSLSTMplus")
Maintained by
Jaime Pizarroso Gonzalo
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-11-21
Latest Update: 2024-02-04
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) <doi:10.1007/s00500-021-06087-4>.
How to cite:
Jaime Pizarroso Gonzalo (2023). TSLSTMplus: Long-Short Term Memory for Time-Series Forecasting, Enhanced. R package version 1.0.5, https://cran.r-project.org/web/packages/TSLSTMplus. Accessed 24 Nov. 2024.
Previous versions and publish date:
1.0.0 (2023-11-21 19:00), 1.0.1 (2023-11-28 02:10), 1.0.2 (2024-01-11 23:50), 1.0.3 (2024-02-04 19:30), 1.0.4 (2024-03-10 20:10)
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Complete documentation for TSLSTMplus
Functions, R codes and Examples using the TSLSTMplus R package
Full TSLSTMplus package functions and examples
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