Gaussian processes with monotonicity information

13th International Conference on Artificial Intelligence and Statistics

计算机科学;数学科学

Jaakko Riihima¨ki Aki Vehtari ; Dept. of Biomedical Engineering

PID  :  119814

来源: CEUR

【 摘 要 】

Amethod for using monotonicity information in multivariate Gaussian process regression and classification is proposed. Monotonicity information is introduced with virtual deriva tive observations, and the resulting posterior is approximated with expectation propaga tion. Behaviour of the method is illustrated with artificial regression examples, and the method is used in a real world health care classification problem to include monotonic ity information with respect to one of the co