Package: WaveletML 0.1.0

WaveletML: Wavelet Decomposition Based Hybrid Machine Learning Models

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>.

Authors:Mr. Sandip Garai [aut, cre], Dr. Ranjit Kumar Paul [aut], Dr. Md Yeasin [aut]

WaveletML_0.1.0.tar.gz
WaveletML_0.1.0.zip(r-4.7)WaveletML_0.1.0.zip(r-4.6)WaveletML_0.1.0.zip(r-4.5)
WaveletML_0.1.0.tgz(r-4.6-any)WaveletML_0.1.0.tgz(r-4.5-any)
WaveletML_0.1.0.tar.gz(r-4.7-any)WaveletML_0.1.0.tar.gz(r-4.6-any)
WaveletML_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
WaveletML/json (API)

# Install 'WaveletML' in R:
install.packages('WaveletML', repos = c('https://sandipgarai.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 packages 154 downloads 2 exports 110 dependencies

Last updated from:639b495984. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK182
source / vignettesOK184
linux-release-x86_64OK195
macos-release-arm64OK128
macos-oldrel-arm64OK163
windows-develOK142
windows-releaseOK168
windows-oldrelOK133
wasm-releaseOK124

Exports:warigaanwarigas

Dependencies:aTSAcaretclasscliclockcodetoolscolorspacecpp11curlcvardata.tableDerivdiagramdigestdplyre1071earthfarverfastICAfBasicsfGarchFinTSforeachforecastFormulafracdifffuturefuture.applygbutilsgenericsggplot2globalsgluegowergssgtablehardhatipredisobanditeratorsjsonliteKernSmoothlabelinglatticelavalifecyclelistenvlmtestLSTSlubridatemagrittrMASSMatrixModelMetricsneuralnetnlmennetnumDerivparallellypatchworkpillarpkgconfigplotmoplotrixplyrpROCprodlimprogressrproxypsopurrrquadprogquantmodR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackrecipesreshape2rlangrpartS7scalesshapesparsevctrsspatialSQUAREMstablediststringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetimeSeriestseriesTTRtzdburcautf8vctrsviridisLitewaveletswithrxtszoo