Package: LOGANTree 0.1.1

Qi Qin

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> .

Authors:Denise Reis Costa [aut, ths], Qi Qin [aut, cre]

LOGANTree_0.1.1.tar.gz
LOGANTree_0.1.1.tar.gz(r-4.5-noble)LOGANTree_0.1.1.tar.gz(r-4.4-noble)
LOGANTree_0.1.1.tgz(r-4.4-emscripten)LOGANTree_0.1.1.tgz(r-4.3-emscripten)
LOGANTree.pdf |LOGANTree.html
LOGANTree/json (API)

# Install 'LOGANTree' in R:
install.packages('LOGANTree', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • cp025q01.features - Data for PISA 2012, CP025, Q01
  • cp025q01.wgt - Treated data for PISA 2012, CP025, Q01
  • testing - PISA 2012, CP025, Q01 (selected countries) Testing Data Set
  • training - PISA 2012, CP025, Q01 (selected countries) Training Data Set

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

13 exports 0.00 score 85 dependencies 215 downloads

Last updated 2 years agofrom:34d244e04a. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 02 2024
R-4.5-linuxOKSep 02 2024

Exports:ChiSquarePlotChiSquareTableComputeChisquaredDataPartitionDtResultNearZeroVariancePartialDependencePlotPerformanceMetricsRocPlotTreeModelsTreeModelsAllStepsVariableImportancePlotVariableImportanceTable

Dependencies:bitopscaretcaretEnsemblecaToolsclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygbmgenericsggplot2globalsgluegowergplotsgtablegtoolshardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypatchworkpbapplypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangROCRrpartrpart.plotscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr