Employing linear regression in regression tree leaves
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Original Contribution: Stacked generalization
Neural Networks
Machine Learning
Recursive Automatic Bias Selection for Classifier Construction
Machine Learning - Special issue on bias evaluation and selection
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Machine Learning
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Functional Models for Regression Tree Leaves
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Linear Machine Decision Trees
A system for induction of oblique decision trees
Journal of Artificial Intelligence Research
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In this paper we present and evaluate a new algorithm for supervised learning regression problems. The algorithm combines a univariate regression tree with a linear regression function by means of constructive induction. When growing the tree, at each internal node, a linear-regression function creates one new attribute. This new attribute is the instantiation of the regression function for each example that fall at this node. This new instance space is propagated down through the tree. Tests based on those new attributes correspond to an oblique decision surface. Our approach can be seen as a hybrid model that combines a linear regression known to have low variance with a regression tree known to have low bias. Our algorithm was compared against to its components, and two simplified versions, and M5 using 16 benchmark datasets. The experimental evaluation shows that our algorithm has clear advantages with respect to the generalization ability when compared against its components and competes well against the state-of-art in regression trees.