In this paper, we review the paradigm of inductive process modeling, which uses background knowledge about possible component processes to construct quantitative models of dynamic...
Will Bridewell, Narges Bani Asadi, Pat Langley, Lj...
We consider online learning where the target concept can change over time. Previous work on expert prediction algorithms has bounded the worst-case performance on any subsequence ...
The availability of techniques for comparing descriptions has many applications in Artificial Intelligence, ranging from description selection to flexible matching, from instance...
Stefano Ferilli, Teresa Maria Altomare Basile, Nic...
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. A common way to measure performance in these domains is to use precision and recall i...
In many applications, good ranking is a highly desirable performance for a classifier. The criterion commonly used to measure the ranking quality of a classification algorithm is ...