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dc.contributor.authorWei, Guangning-
dc.date.accessioned2021-07-13T12:58:27Z-
dc.date.available2021-07-13T12:58:27Z-
dc.date.issued2021-06-17-
dc.identifier.urihttp://hdl.handle.net/2451/62799-
dc.description.abstractAbstract This project aims to use R language to develop a decision-tree module that is working correctly under software Jamovi. This project will create an easy teaching tool for the NYU MASY program, allowing faculties and students to do decision-tree analysis without typing R codes by themselves. Also, they may just import the data into Jamovi and use the decision-tree module to perform analysis. This module will be developed by following the Jamovi module creation tutorials; all the R codes will be written in R studio within the requirement of the Jamovi environment (jmvcore, jmvtools). The required R packages knowledge of decision-tree module development are R6, caret, rpart, class, and rpart.plot. These R packages were mainly used when developing the decision-tree module The client of this project will have full access to the Jamovi module from the GitHub repository (link:https://github.com/guangningwei?tab=repositories). The descriptions on GitHub will guide the users on installing and using the module on both Windows-based PCs and Apple Macs to eliminate the difficulties of finding an appropriate platform. On the other hand, this module could be used by those who may use it for research purposes. At last, the project is costeffective with no extra costs.en
dc.description.sponsorshipNYU School of Professional Studies MASY Programen
dc.language.isoen_USen
dc.rightsAuthor Reserves All Rightsen
dc.subjectDecision Tree, Random Forst, R, Jamovien
dc.titleDecision Tree Analyzeren
dc.typeWorking Paperen
Appears in Collections:MASY Student Research Showcase 2021

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Guangning Wei - Final Report - Decision Tree Analyzer.pdfAbstract This project aims to use R language to develop a decision-tree module that is working correctly under software Jamovi. This project will create an easy teaching tool for the NYU MASY program, allowing faculties and students to do decision-tree analysis without typing R codes by themselves. Also, they may just import the data into Jamovi and use the decision-tree module to perform analysis. This module will be developed by following the Jamovi module creation tutorials; all the R codes will be written in R studio within the requirement of the Jamovi environment (jmvcore, jmvtools). The required R packages knowledge of decision-tree module development are R6, caret, rpart, class, and rpart.plot. These R packages were mainly used when developing the decision-tree module The client of this project will have full access to the Jamovi module from the GitHub repository (link:https://github.com/guangningwei?tab=repositories). The descriptions on GitHub will guide the users on installing and using the module on both Windows-based PCs and Apple Macs to eliminate the difficulties of finding an appropriate platform. On the other hand, this module could be used by those who may use it for research purposes. At last, the project is costeffective with no extra costs.13.14 MBAdobe PDFView/Open


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