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What is Mixed Decision Tree

Encyclopedia of Information Science and Technology, Fourth Edition
A decision tree with heterogeneous representation. The tests in internal nodes may be univariate or multivariate whereas the leaves may hold a constant value or a regression model.
Published in Chapter:
Evolutionary Algorithms for Global Decision Tree Induction
Marek Kretowski (Bialystok University of Technology, Poland) and Marcin Czajkowski (Bialystok University of Technology, Poland)
Copyright: © 2018 |Pages: 10
DOI: 10.4018/978-1-5225-2255-3.ch185
Abstract
Decision trees represent one of the main predictive techniques in knowledge discovery. This chapter describes evolutionary induced trees, which are emerging alternatives to the greedy top-down solutions. Most typical tree-based system searches only for locally optimal decisions at each node and do not guarantee the optimal solution. Application of evolutionary algorithms to the problem of decision tree induction allows searching for the structure of the tree, tests in internal nodes and regression functions in the leaves (for model trees) at the same time. As a result, such globally induced decision tree is able to avoid local optima and usually leads to better prediction than the greedy counterparts.
Full Text Chapter Download: US $37.50 Add to Cart
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Evolutionary Algorithms for Global Decision Tree Induction
A decision tree with heterogeneous representation. The tests in internal nodes may be univariate or multivariate whereas the leaves may hold a constant value or a regression model.
Full Text Chapter Download: US $37.50 Add to Cart
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