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Modified classification and regression tree splitting criteria for data with interactions
Journal article   Peer reviewed

Modified classification and regression tree splitting criteria for data with interactions

A.P. Bremner and R.H. Taplin
Australian & New Zealand Journal of Statistics, Vol.44(2), pp.169-176
2002
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Abstract

This paper proposes modified splitting criteria for classification and regression trees by modifying the definition of the deviance. The modified deviance is based on local averaging instead of global averaging and is more successful at modelling data with interactions. The paper shows that the modified criteria result in much simpler trees for pure interaction data (no main effects) and can produce trees with fewer errors and lower residual mean deviances than those produced by Clark & Pregibon’s (1992) method when applied to real datasets with strong interaction effects.

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Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.61 Artificial Intelligence & Machine Learning
4.61.145 Classification Algorithms
Web Of Science research areas
Statistics & Probability
ESI research areas
Mathematics
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