PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Optimal Constraint-based Decision Tree Induction from Itemset Lattices
Elisa Fromont and Siegfried Nijssen
Data Mining and Knowledge Discovery 2009.

Abstract

In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard problem of finding optimal decision trees in a wide range of applications by postprocessing a set of patterns: we use local patterns to construct a global model.We exploit the connection between constraints in pattern mining and constraints in decision tree induction to develop a framework for categorizing decision tree mining constraints. This framework allows us to determine which model constraints can be pushed deeply into the pattern mining process, and allows us to improve the state-of-the-art of optimal decision tree induction.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5764
Deposited By:Elisa Fromont
Deposited On:08 March 2010