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Evaluation of open source data mining software packagesAuthor(s): Bonnie Ruefenacht; Greg Liknes; Andrew J. Lister; Haans Fisk; Dan Wendt
Source: In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 13 p.
Publication Series: Proceedings (P)
Station: Rocky Mountain Research Station
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DescriptionSince 2001, the USDA Forest Service (USFS) has used classification and regression-tree technology to map USFS Forest Inventory and Analysis (FIA) biomass, forest type, forest type groups, and National Forest vegetation. This prior work used Cubist/See5 software for the analyses. The objective of this project, sponsored by the Remote Sensing Steering Committee (RSSC), was to evaluate other software packages, including R, SAS, WEKA, and Orange. These software packages must work with the USFS standard remote-sensing and GIS packages such as ArcGIS and ERDAS Imagine. As part of this project, a Python script was developed that fully integrated these software packages, excluding SAS, with ArcGIS and ERDAS Imagine. Appendix A provides the tutorial for this script. Appendix B provides a tutorial on how to write similar scripts in Python.
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CitationRuefenacht, Bonnie; Liknes, Greg; Lister, Andrew J.; Fisk, Haans; Wendt, Dan. 2009. Evaluation of open source data mining software packages. In: McWilliams, Will; Moisen, Gretchen; Czaplewski, Ray, comps. Forest Inventory and Analysis (FIA) Symposium 2008; October 21-23, 2008; Park City, UT. Proc. RMRS-P-56CD. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 13 p.
KeywordsCART, Orange, WEKA, R, random forest, classification trees, regression trees, open-source software
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