Package: ModelMap 3.4.0.4
Elizabeth Freeman
ModelMap: Modeling and Map Production using Random Forest and Related Stochastic Models
Creates sophisticated models of training data and validates the models with an independent test set, cross validation, or Out Of Bag (OOB) predictions on the training data. Create graphs and tables of the model validation results. Applies these models to GIS .img files of predictors to create detailed prediction surfaces. Handles large predictor files for map making, by reading in the .img files in chunks, and output to the .txt file the prediction for each data chunk, before reading the next chunk of data.
Authors:
ModelMap_3.4.0.4.tar.gz
ModelMap_3.4.0.4.tar.gz(r-4.5-noble)ModelMap_3.4.0.4.tar.gz(r-4.4-noble)
ModelMap_3.4.0.4.tgz(r-4.4-emscripten)ModelMap_3.4.0.4.tgz(r-4.3-emscripten)
ModelMap.pdf |ModelMap.html✨
ModelMap/json (API)
# Install 'ModelMap' in R: |
install.packages('ModelMap', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:19266adc02. Checks:OK: 1 NOTE: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 09 2024 |
R-4.5-linux | NOTE | Dec 09 2024 |
Exports:build.rastLUTCF.binaryCF.categoricalCF.continuousCF.int2numCF.list2dfcheck.device.typecheck.device.type.nodefaultcheck.model.levelscheck.model.typecheck.predListcheck.response.namecheck.response.typecol2transcorrelation.functioncreate.modeldiagnostics.functionexplore.categoricalexplore.continuousFNcheckget.testgetRastsgrd2griimp.extract.cfimp.extract.qrfimp.extract.rfimp.scaleinitialize.devicemask.funmask.graphicmodel.buildmodel.diagnosticsmodel.exploremodel.importance.plotmodel.interaction.plotmodel.mapmakeprediction.CF.binaryprediction.CF.categoricalprediction.CF.continuousprediction.modelprediction.rF.binaryprediction.rF.categoricalprediction.rF.continuousprediction.rF.quantregproduction.predictionprojcompareprojfixREQUIRE.partyREQUIRE.quantregForestrF.binaryrF.categoricalrF.continuousrF.quantreg
Dependencies:corrplotdotCall64fieldsHandTill2001latticemapsMatrixmgcvnlmePresenceAbsencerandomForestrasterRcppspspamterraviridisLite
Exploratory Data Analysis with the ModelMap package
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Pick your flavor of Random Forest
Rendered fromVquantile.Rnw
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Readme and manuals
Help Manual
Help page | Topics |
---|---|
Modeling and Map Production using Random Forest and Related Stochastic Models | ModelMap-package ModelMap |
Build a raster Look-UP-Table for training dataset | build.rastLUT |
colors to transparent colors | col2trans |
Randomly Divide Data into Training and Test Sets | get.test |
Model Building | model.build |
Model Predictions and Diagnostics | model.diagnostics |
Exploratory data analysis | model.explore |
Compares the variable importance of two models with a back to back barchart. | model.importance.plot |
plot of two-way model interactions | model.interaction.plot |
Map Making | model.mapmake |