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WaveletLSTM  

Wavelet Based LSTM Model
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("WaveletLSTM", "0.1.0")



Attach the package and use:
library("WaveletLSTM")
Maintained by
Dr. Md Yeasin
[Scholar Profile | Author Map]
First Published: 2023-04-06
Latest Update: 2023-04-06
Description:
A wavelet-based LSTM model is a type of neural network architecture that uses wavelet technique to pre-process the input data before passing it through a Long Short-Term Memory (LSTM) network. The wavelet-based LSTM model is a powerful approach that combines the benefits of wavelet analysis and LSTM networks to improve the accuracy of predictions in various applications. This package has been developed using the algorithm of Anjoy and Paul (2017) and Paul and Garai (2021) <doi:10.1007/s00521-017-3289-9> <doi:10.1007/s00500-021-06087-4>.
How to cite:
Dr. Md Yeasin (2023). WaveletLSTM: Wavelet Based LSTM Model. R package version 0.1.0, https://cran.r-project.org/web/packages/WaveletLSTM. Accessed 21 Feb. 2025.
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Complete documentation for WaveletLSTM
Functions, R codes and Examples using the WaveletLSTM R package
Full WaveletLSTM package functions and examples
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