training

<p>A training set partitioned from the cp025q01.wgt dataset with 70</p>

datasets

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> .

Qi Qin

LOGANTree

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

Denise Reis Costa

training function

<p>A data frame with 1020 rows and 14 variables.</p>

training: PISA 2012, CP025, Q01 (selected countries) Training Data Set

Description

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