Integrating Expert Knowledge with Data in Bayesian Networks: Preserving Data-Driven Expectations when the Expert Variables Remain Unobserved
نویسنده
چکیده
a. Risk and Information Management (RIM) Research Group, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK, E1 4NS. b. Corresponding author. E-mail address: [email protected] c. Director of Risk and Information Management (RIM) Research Group, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK, E1 4NS. E-mail: [email protected] d. Director, Agena Ltd, Cambridge, UK, CB23 7NU. e. Risk and Information Management (RIM) Research Group, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK, E1 4NS. E-mail: [email protected] f. Director, Agena Ltd, Cambridge, UK, CB23 7NU.
منابع مشابه
Integrating Expert Knowledge with Data in Bayesian Networks: Preserving Data-Driven Expectations when the Expert Variables Remain Unobserved
When developing a causal probabilistic model, i.e. a Bayesian network (BN), it is common to incorporate expert knowledge of factors that are important for decision analysis but where historical data are unavailable or difficult to obtain. This paper focuses on the problem whereby the distribution of some continuous variable in a BN is known from data, but where we wish to explicitly model the i...
متن کاملAn interactive approach for Bayesian network learning using domain/expert knowledge
Using domain/expert knowledge when learning Bayesian networks from data has been considered a promising idea since the very beginning of the field. However, in most of the previously proposed approaches, human experts do not play an active role in the learning process. Once their knowledge is elicited, they do not participate any more. The interactive approach for integrating domain/expert know...
متن کاملThe modeling of body's immune system using Bayesian Networks
In this paper, the urinary infection, that is a common symptom of the decline of the immune system, is discussed based on the well-known algorithms in machine learning, such as Bayesian networks in both Markov and tree structures. A large scale sampling has been executed to evaluate the performance of Bayesian network algorithm. A number of 4052 samples wereobtained from the database of the Tak...
متن کاملLearning Parameters for a Knowledge Diagnostic Tools in Orthopedic Surgery
We provide and illustrate a methodology for taking into account data for a knowledge diagnosis method in orthopaedical surgery, using Bayesian networks and machine learning techniques. We aim to make the conception of the student model less time-consuming and subjective. A first Bayesian network was built like an expert system, where experts (in didactic and surgery) provide both the structure ...
متن کاملEffective Bayesian Modelling with Knowledge before Data
This project aims to improve evidence-based decision-making. What makes it radical is that it plans to do this in situations (common for critical risk assessment problems) where there is little or even no data, and hence where traditional statistics cannot be used. To address this problem Bayesian analysis, which enables domain experts to supplement observed data with subjective probabilities, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016