Data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. In this paper, we prove...
Background: Non-homology based methods such as phylogenetic profiles are effective for predicting functional relationships between proteins with no considerable sequence or struct...
Ryosuke Watanabe, Enrique Morett, Edgar E. Vallejo
We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
It has been observed that traditional decision trees produce poor probability estimates. In many applications, however, a probability estimation tree (PET) with accurate probabilit...
We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...