关键词：电子信息；计算机；辅助预知；不确定性
摘 要：Multivariate regression models are often used for the purpose of prognosis. Parameters of such models are estimated on the basis of learning sets, where feature vectors (independent variables) are combined with values of response (target) variable. The values of response variable can be determined only with some uncertainty in some important applications. For example, in survival analysis, the values of response variable is often censored and can be represented as intervals. The interval regression approach has been proposed for designing prognostic tools in circumstances of such type of uncertainty. The possibility of using the convex and piecewise linear (CPL) functions in designing linear prognostic models on the basis of interval learning sets is examined in the paper.