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-any)WaveletML_0.1.0.zip(r-4.6-any)WaveletML_0.1.0.zip(r-4.5-any)
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✨
DESCRIPTION
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 238 downloads 2 exports 110 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK213
source / vignettesOK223
linux-releaseOK198
macos-releaseOK132
macos-oldrelOK139
windows-develOK133
windows-releaseOK136
windows-oldrelOK125
wasm-releaseOK142

Exports:warigaanwarigas

Dependencies:aTSAcaretclasscliclockcodetoolscolorspacecpp11curlcvardata.tableDerivdiagramdigestdplyre1071earthfarverfastICAfBasicsfGarchFinTSforeachforecastFormulafracdifffuturefuture.applygbutilsgenericsggplot2globalsgluegowergssgtablehardhatipredisobanditeratorsjsonliteKernSmoothlabelinglatticelavalifecyclelistenvlmtestLSTSlubridatemagrittrMASSMatrixModelMetricsneuralnetnlmennetnumDerivparallellypatchworkpillarpkgconfigplotmoplotrixplyrpROCprodlimprogressrproxypsopurrrquadprogquantmodR6rbibutilsRColorBrewerRcppRcppArmadilloRdpackrecipesreshape2rlangrpartS7scalesshapesparsevctrsspatialSQUAREMstablediststringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetimeSeriestseriesTTRtzdburcautf8vctrsviridisLitewaveletswithrxtszoo