کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
383752 | 660832 | 2014 | 18 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Physarum Learner: A bio-inspired way of learning structure from data Physarum Learner: A bio-inspired way of learning structure from data](/preview/png/383752.png)
• A new bio-inspired optimization algorithm is presented.
• It extends the Physarum Solver algorithm.
• It learns Bayesian Network structure from data.
• The algorithm’s performance is shown on artificial and real benchmark networks.
A novel Score-based Physarum Learner algorithm for learning Bayesian Network structure from data is introduced and shown to outperform common score based structure learning algorithms for some benchmark data sets. The Score-based Physarum Learner first initializes a fully connected Physarum-Maze with random conductances. In each Physarum Solver iteration, the source and sink nodes are changed randomly, and the conductances are updated. Connections exceeding a predefined conductance threshold are considered as Bayesian Network edges, and the score of the connected nodes are examined in both directions. A positive or negative feedback is given to the edge conductance based on the calculated scores. Due to randomness in selecting connections for evaluation, an ensemble of Score-based Physarum Learner is used to build the final Bayesian Network structure.
Journal: Expert Systems with Applications - Volume 41, Issue 11, 1 September 2014, Pages 5353–5370