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ImHD: Artificial Intelligence Based Machine Learning Algorithms for Height Diameter Relationships of Conifer Trees

Estimating height of forest plant is one of the key challenges of recent times. This package will help to fit and validate AI (Artificial Intelligence) based machine learning algorithms for estimation of height of conifer trees based on diameter at breast height as explanatory variable using algorithm of Paul et al. (2022) <doi:10.1371/journal.pone.0270553>..

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: stats, randomForest, e1071, xgboost, ggplot2, reshape2, rpart
Published: 2023-09-12
DOI: 10.32614/CRAN.package.ImHD
Author: Dr. M. Iqbal Jeelani [aut, cre], Dr. Fehim Jeelani [aut], Dr. Shakeel Ahmad Mir [aut], Dr. Syed Naseem Geelani [aut], Dr. Mushtaq Ahmad Lone [aut], Dr. Asif Ali [aut], Dr. Tahir Mushtaq [aut], Dr. Amir Bhat [aut], Dr. Md Yeasin [aut]
Maintainer: Dr. M. Iqbal Jeelani <jeelani.miqbal at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: ImHD results

Documentation:

Reference manual: ImHD.pdf

Downloads:

Package source: ImHD_0.1.0.tar.gz
Windows binaries: r-devel: ImHD_0.1.0.zip, r-release: ImHD_0.1.0.zip, r-oldrel: ImHD_0.1.0.zip
macOS binaries: r-release (arm64): ImHD_0.1.0.tgz, r-oldrel (arm64): ImHD_0.1.0.tgz, r-release (x86_64): ImHD_0.1.0.tgz, r-oldrel (x86_64): ImHD_0.1.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.