Reasoning and Learning of the Parameters in Continuous Causality Diagram
Hongchun Wang · Microelectronics & Computer · 2007
Causality diagram theory is a methodology based on probability theory, which adopted graphical expression of knowledge and direct causal intensity of causality. The probability density function of linkage events is the basis of the inference. But it is difficult to give it by expert In the paper, we discuss the approaches to learn the parameters (probability density function of linkage events) from a set of data, given a fixed network structure, by the parametric, non-parametric and semi- parametric methods.