Student and school performance across countries: a machine learning approach
type: Item
instance of: scholarly article
title: Student and school performance across countries: a machine learning approach
zbMATH Open document ID: 1388.62378
author: Chiara Masci
author: Geraint Johnes
author: Tommaso Agasisti
published in: European Journal of Operational Research
publication date: 2018-05-17T00:00:00Z
full work available at URL: article Masci 2018.pdf
Mathematics Subject Classification ID: 62P25
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 90B90
zbMATH DE Number: 6869351
zbMATH Keywords: education
zbMATH Keywords: multilevel model
zbMATH Keywords: school value-added
zbMATH Keywords: regression trees
zbMATH Keywords: boosting
describes a project that uses: R
MaRDI profile type: Publication
OpenAlex ID: W2788255612
cites work: Heterogeneity, school-effects and the north/south achievement gap in Italian secondary education: evidence from a three-level mixed model
cites work: Random forests
cites work: Q3327527
cites work: An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market
cites work: Greedy function approximation: A gradient boosting machine.
cites work: An Introduction to Statistical Learning
cites work: Bivariate multilevel models for the analysis of mathematics and reading pupils' achievements
cites work: Hedge fund systemic risk signals
cites work: Q5386442
cites work: RE-EM trees: a data mining approach for longitudinal and clustered data
DOI: 10.1016/J.EJOR.2018.02.031
description: scientific article; zbMATH DE number 6869351