Title :
An Algorithm for Bayesian Networks Structure Learning Based on Simulated Annealing with MDL Restriction
Author :
Ye, Shuisheng ; Cai, Hong ; Sun, Rongguan
Author_Institution :
Coll. of Comput., Nanchang Hongkong Univ., Nanchang
Abstract :
By means of deducing and analyzing the minimum description length (MDL) principle as the grading functions, this paper designs a maximum entropy grade-function with complexity restriction, and proposes an algorithm for structure learning in Bayesian networks based on simulated annealing. Then according to the analysis of the historical stock data with this algorithm, the topological structure of network is obtained and so is conditional probability table of every network node. At last, the trend and fluctuation interval of the stock price are forecasted by this Bayesian model.
Keywords :
Bayes methods; maximum entropy methods; pricing; simulated annealing; stock markets; Bayesian networks structure learning; MDL restriction; complexity restriction; grading functions; historical stock data; maximum entropy grade-function; minimum description length; simulated annealing; stock price; Algorithm design and analysis; Analytical models; Bayesian methods; Computational modeling; Computer networks; Entropy; Fluctuations; Network topology; Predictive models; Simulated annealing; Bayesian Networks (BN); MDL; simulated annealing; stock forecasting;
Conference_Titel :
Natural Computation, 2008. ICNC '08. Fourth International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-0-7695-3304-9
DOI :
10.1109/ICNC.2008.658
