Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
Users often can not easily express their queries. For example, in a multimedia image by content setting, the user might want photographs with sunsets; in current systems, like QBI...
We study the behavior of random walks along the edges of the stable marriage lattice for various restricted families of allowable preference sets. In the "k-attribute model,&...
Background: Random forests (RF) have been increasingly used in applications such as genome-wide association and microarray studies where predictor correlation is frequently observ...
Kristin K. Nicodemus, James D. Malley, Carolin Str...
Background: Molecular interaction networks can be efficiently studied using network visualization software such as Cytoscape. The relevant nodes, edges and their attributes can be...
Kris Laukens, Jens Hollunder, Thanh Hai Dang, Geer...