1 research outputs found
Regression trees for multivalued numerical response variables
In the framework of regression trees, this paper provides a recursive partitioning
methodology to deal with a non-standard response variable. Specifically, either
multivalued numerical or modal response of the type histogram will be considered.
These data are known as symbolic data, which special cases are classical
data, imprecise data, conjunctive data as well as fuzzy data. In spite of preprocessing
data in order to deal with standard regression tree methodology, this
paper provides, as main contribution, a definition of the impurity measure and
of the splitting criterion allowing for building the regression tree for multivalued
numerical response variable. We analyze and evaluate the performance of our
proposal, using simulated data as well as a real-world case studies