The autoregressive HMM has been shown to provide efficient parameter estimation and high-quality synthesis, but in previous experiments decision trees derived from a non-autoregre...
ABSTRACT. This paper introduces a tree-based model that combines aspects of CART (Classification and Regression Trees) and STR (Smooth Transition Regression). The model is called t...
We present an empirical comparison of the AUC performance of seven supervised learning methods: SVMs, neural nets, decision trees, k-nearest neighbor, bagged trees, boosted trees,...
An important drawback to the popular Belief, Desire, and Intentions (BDI) paradigm is that such systems include no element of learning from experience. In particular, the so-calle...
Microarray experiments are emerging as one of the main driving forces in modern biology. By allowing the simultaneous monitoring of the expression of the entire genome for a given...