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WaveletML
View on CRAN: Click
here
Download and install WaveletML package within the R console
Install from CRAN:
install.packages("WaveletML")
Install from Github:
library("remotes")
install_github("cran/WaveletML")
Install by package version:
library("remotes")
install_version("WaveletML", "0.1.0")
Attach the package and use:
library("WaveletML")
Maintained by
Mr. Sandip Garai
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.WaveletML . WaveletML results . WaveletML.pdf . WaveletML_0.1.0.tar.gz . WaveletML_0.1.0.zip . WaveletML_0.1.0.zip . WaveletML_0.1.0.zip . WaveletML_0.1.0.tgz . WaveletML_0.1.0.tgz . WaveletML_0.1.0.tgz . WaveletML_0.1.0.tgz . WaveletML_0.1.0.tgz . WaveletML_0.1.0.tgz . WaveletMLbestFL . https://CRAN.R-project.org/package=WaveletML .
First Published: 2023-04-05
Latest Update: 2023-04-05
Description:
Wavelet decomposes a series into multiple sub series called detailed and smooth components which helps to capture volatility at multi resolution level by various models. Two hybrid Machine Learning (ML) models (Artificial Neural Network and Support Vector Regression have been used) have been developed in combination with stochastic models, feature selection, and optimization algorithms for prediction of the data. The algorithms have been developed following Paul and Garai (2021)<doi:10.1007/s00500-021-06087-4>.
How to cite:
Mr. Sandip Garai (2023). WaveletML: Wavelet Decomposition Based Hybrid Machine Learning Models. R package version 0.1.0, https://cran.r-project.org/web/packages/WaveletML. Accessed 02 Apr. 2025.
Previous versions and publish date:
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