@article{2467,
  keywords = {Bayesian Network, Evolutionary Algorithm, PBIL},
  author = {Sho Fukuda and Yuuma Yamanaka and Takuya Yoshihiro},
  title = {A Probability-based Evolutionary Algorithm with Mutations to Learn Bayesian Networks},
  abstract = {Bayesian networks are regarded as one of the essential tools to analyze causal relationship between events from data. To learn the structure of highly-reliable Bayesian networks from data as quickly as possible is one of the important problems that several studies have been tried to achieve. In recent years, probability-based evolutionary algorithms have been proposed as a new efficient approach to learn Bayesian networks. In this paper, we target on one of the probability-based evolutionary algorithms called PBIL (Probability-Based Incremental Learning), and propose a new mutation operator. Through performance evaluation, we found that the proposed mutation operator has a good performance in learning Bayesian networks},
  year = {2014},
  journal = {International Journal of Interactive Multimedia and Artificial Intelligence},
  volume = {3},
  number = {1},
  pages = {7-13},
  month = {12/2014},
  issn = {1989-1660},
  url = {http://www.ijimai.org/journal/sites/default/files/files/2014/11/ijimai20143_1_1_pdf_24199.pdf},
  doi = {10.9781/ijimai.2014.311},
}