We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Schlumberger RPS successfully applies software measurement to support their software development projects. It is proposed that the success of their measurement practices is mainly...
Ordering information is a difficult but a important task for natural language generation applications. A wrong order of information not only makes it difficult to understand, but a...
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...