LOGANTree: Tree-Based Models for the Analysis of Log Files from Computer-Based Assessments

Enables researchers to model log-file data from computer-based assessments using machine-learning techniques. It allows researchers to generate new knowledge by comparing the performance of three tree-based classification models (i.e., decision trees, random forest, and gradient boosting) to predict student's outcome. It also contains a set of handful functions for the analysis of the features' influence on the modeling. Data from the Climate control item from the 2012 Programme for International Student Assessment (PISA, <https://www.oecd.org/pisa/>) is available for an illustration of the package's capability. He, Q., & von Davier, M. (2015) <doi:10.1007/978-3-319-19977-1_13> Boehmke, B., & Greenwell, B. M. (2019) <doi:10.1201/9780367816377> .

Version: 0.1.1
Depends: R (≥ 3.5.0)
Imports: ROCR, caret, caretEnsemble, dplyr, ggplot2, rpart.plot, tibble, gbm, stats
Published: 2022-06-22
Author: Denise Reis Costa [aut, ths], Qi Qin [aut, cre]
Maintainer: Qi Qin <logantreeqq at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: LOGANTree results


Reference manual: LOGANTree.pdf


Package source: LOGANTree_0.1.1.tar.gz
Windows binaries: r-devel: LOGANTree_0.1.1.zip, r-release: LOGANTree_0.1.1.zip, r-oldrel: LOGANTree_0.1.1.zip
macOS binaries: r-release (arm64): LOGANTree_0.1.1.tgz, r-oldrel (arm64): LOGANTree_0.1.1.tgz, r-release (x86_64): LOGANTree_0.1.1.tgz, r-oldrel (x86_64): LOGANTree_0.1.1.tgz
Old sources: LOGANTree archive


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