R 4.2.x no longer provides a 32-bit version of the Software and only ships a 64-bit version. Because of this, R 4.2 and later won't work with ArcMap except through background geoprocessing. ArcGIS Pro is a 64-bit application and will work without additional steps for R 4.2, or, as you did, continue using R 4.1, which still provides a 32-bit version in the installation. (https://github.com/emrehanks/R-ArcGIS-LSM_ToolPack-64bit)
Two new modeling methods were added in The LSM_ToolPack namely, Support Vector Machine (SVM) and eXtreme gradient boosting (XGBoost)
Dear Users, Don't forget to follow the "Issues" tab for important announcements!
Released version of the LSM Tool Pack supporting R 4.2.x and ArcGIS Pro
If you meet the error code given below, please unzip this "recipes" file on your base R location (e.g. C:\Users\emrehan\OneDrive\Documents\R\win-library\3.6)
"Error: package or namespace load failed for ‘caret’ in loadNamespace(i, c(lib.loc, .libPaths()), versionCheck = vI[[i]]): there is no package called ‘recipes’*"
If you meet the error code given below, use ArcGIS Pro 2 or downgrade the latest R-Base version 4 to 3.6.3.
"Failed to initialize R interpreter*"
This clip shows you how to divide your data train and validation data:
This clip shows you how to use the module for selecting the best feature subset:
This clip shows you how to use the LR algortihm for produce susceptibility map. This module provides the user statistical results and LR model ROC curve and AUC value.
This clip shows you how to use the tool: This module provides the user RF feature importance results as an excel sheet paper and RF model ROC curve and AUC value as a 300dpi TIFF image.
This clip shows you how to use the tool: This module provides the user accuracy metric results (Overall accuracy, Kappa, AUC, and F1 values) as an excel sheet paper.
This clip shows you how to use the tool: this module transforms your single factor maps into raster stack map.
LSM Tool Pack was prepared as part of the projects “Development of ArcGIS Interfaces with R programming language for Landslide Susceptibility Mapping” (No. 118Y090) funded by The Scientific and Technological Research Council of Turkey (TUBITAK).
Emrehan Kutlug Sahin, Ismail Colkesen, Suheda Semih Acmali, Aykut Akgun, Arif Cagdas Aydinoglu, Developing comprehensive geocomputation tools for landslide susceptibility mapping: LSM tool pack, Computers & Geosciences, 2020, 104592, ISSN 0098-3004, https://doi.org/10.1016/j.cageo.2020.104592. (http://www.sciencedirect.com/science/article/pii/S009830042030577X)