Research on Orienting Edges of Bayesian Network Based on Information Theory and Genetic Algorithms
LI Xiao-lin · Fudan xuebao. Ziran Kexue ban · 2004
Orienting edges of Bayesian network is part and parcel of learning Bayesian Network. An algorithm is proposed based on information theory and genetic algorithms. Cross-entropy is introduced in learning Bayesian network. Based on the network which oriented edges with cross-entropy, fitness function and genetic operators are designed, it provides guarantee of convergence. This algorithm can weaken the dependence of initial population and increase the convergence speed. Experimental result shows that this algorithm can effectively orient edges of Bayesian network.