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Splitting matters: how monotone transformation of predictor variables
  may improve the predictions of decision tree models

Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models

14 November 2016
Tal Galili
I. Meilijson
ArXivPDFHTML

Papers citing "Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models"

1 / 1 papers shown
Title
ranger: A Fast Implementation of Random Forests for High Dimensional
  Data in C++ and R
ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R
Marvin N. Wright
A. Ziegler
113
2,735
0
18 Aug 2015
1