TY - UNPB
T1 - Evaluating Model-based Trees in Practice
AU - Zeileis, Achim
AU - Hothorn, Torsten
AU - Hornik, Kurt
PY - 2006
Y1 - 2006
N2 - A recently suggested algorithm for recursive partitioning of statistical models (Zeileis, Hothorn and Hornik, 2005), such as models estimated by maximum likelihood or least squares, is evaluated in practice. The general algorithm is applied to linear regression, logisitic regression and survival regression and applied to economical and medical regression problems. Furthermore, its performance with respect to prediction quality and model complexity is compared in a benchmark study with a large collection of other tree-based algorithms showing that the algorithm yields interpretable trees, competitive with previously suggested approaches.
AB - A recently suggested algorithm for recursive partitioning of statistical models (Zeileis, Hothorn and Hornik, 2005), such as models estimated by maximum likelihood or least squares, is evaluated in practice. The general algorithm is applied to linear regression, logisitic regression and survival regression and applied to economical and medical regression problems. Furthermore, its performance with respect to prediction quality and model complexity is compared in a benchmark study with a large collection of other tree-based algorithms showing that the algorithm yields interpretable trees, competitive with previously suggested approaches.
U2 - 10.57938/e1011e48-19d8-4fbd-8e31-9fe761d8a167
DO - 10.57938/e1011e48-19d8-4fbd-8e31-9fe761d8a167
M3 - WU Working Paper and Case
T3 - Research Report Series / Department of Statistics and Mathematics
BT - Evaluating Model-based Trees in Practice
PB - Department of Statistics and Mathematics, WU Vienna University of Economics and Business
CY - Wien
ER -