Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
The purpose of the chapter is to help someone familiar with DLs to understand the issues involved in developing an ontology for some universe of discourse, which is to become a co...
Most studies modeling inaccurate data in Gold style learning consider cases in which the number of inaccuracies is finite. The present paper argues that this approach is not reaso...
Interval number is a kind of special fuzzy number and the interval approach is a good method to deal with some uncertainty. The semi-absolute deviation risk function is extended to...
The prediction of gene function from genome sequences is one of the main issues in Bioinformatics. Most computational approaches are based on the similarity between sequences to in...