Estimating student retention and degree‐completion time: Decision trees and neural networks vis‐à‐vis regression
- 1 September 2006
- journal article
- Published by Wiley in New Directions for Institutional Research
- Vol. 2006 (131), 17-33
- https://doi.org/10.1002/ir.185
Abstract
No abstract availableKeywords
This publication has 10 references indexed in Scilit:
- Measuring Determinants of Student Return VS. Dropout/Stopout VS. Transfer: A First-to-Second Year Analysis of New FreshmenResearch in Higher Education, 2005
- Does College Still Pay?The Economists' Voice, 2005
- Boosted decision trees as an alternative to artificial neural networks for particle identificationNuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 2005
- What Satisfies Students? Mining Student-Opinion Data with Regression and Decision Tree AnalysisResearch in Higher Education, 2004
- Artificial Neural Networks: A New Approach to Predicting Application BehaviorResearch in Higher Education, 2002
- 10.1162/153244304322972694Applied Physics Letters, 2000
- A comparison of conventional linear regression methods and neural networks for forecasting educational spendingEconomics of Education Review, 1999
- Popular Ensemble Methods: An Empirical StudyJournal of Artificial Intelligence Research, 1999
- Automatic Construction of Decision Trees from Data: A Multi-Disciplinary SurveyData Mining and Knowledge Discovery, 1998
- A Comparison of Logistic Regression to Decision-Tree Induction in a Medical DomainComputers and Biomedical Research, 1993