This paper studies the addition of linear constraints to Support Vector Regression when kernel is linear. Adding those into problem allows add prior knowledge on estimator obtained, such as finding positive vector, probability vector or monotone data. We prove that related optimization stays a semi-definite quadratic problem. also propose generalization Sequential Minimal Optimization algorithm...

a number of 5558 lambing records of 2245 mehraban ewes, collected during years 1995 to 2010 were utilized to estimate the variance components and heritability for the number of lambs per lambing,  making use of b-spline random regression models. the fixed factors affecting the studied trait were identified using general linear model analysis as well as sas software, where flock-year-season and ...