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Linear Discriminant Trees Olcay Taner Y ld z yildizol@cmpe.boun.edu.tr
 

Summary: Linear Discriminant Trees
Olcay Taner Yldz yildizol@cmpe.boun.edu.tr
Ethem Alpaydn alpaydin@boun.edu.tr
Department of Computer Engineering, Bogazici University, 80815 _
Istanbul Turkey
Abstract
Univariate decision trees at each decision
node consider the value of only one feature
leading to axis-aligned splits. In a multi-
variate decision tree, each decision node di-
vides the input space into two with an ar-
bitrary hyperplane leading to oblique splits.
In this paper, we propose linear discriminant
trees where each node implements Fisher's
linear discriminant analysis (LDA) to make
a binary split. On twenty data sets from
the UCI repository, we compare the linear
discriminant trees with the univariate deci-
sion tree method ID3, multivariate decision
tree methods CART, neural trees and linear

  

Source: Alpaydın, Ethem - Department of Computer Engineering, Bogaziçi University

 

Collections: Computer Technologies and Information Sciences