Post by Sapphire Capital on Aug 28, 2008 19:51:48 GMT 4
Integrating Neural Networks for Risk-Adjustment Models
Shuofen Hsu
Chaohsin Lin
Yaling Yang
Journal of Risk & Insurance, Vol. 75, Issue 3, pp. 617-642, September 2008
Abstract:
This article demonstrates the possibility of an alternative approach for risk-adjustment models. In the proposed model the risk characteristics of the beneficiary's health within the same cohort classified by Self-Organizing Map network are highly homogeneous, whereas the numbers of individuals within each cohort remain sufficient to allow further investigation of the causal effect from clustered data. A comparison of different models by the 10-fold cross-validation reveals that the performance improvement in the proposed integration model is both significant and stable across the estimation and validation sampling.
papers.ssrn.com/sol3/papers.cfm?abstract_id=1202445
Shuofen Hsu
Chaohsin Lin
Yaling Yang
Journal of Risk & Insurance, Vol. 75, Issue 3, pp. 617-642, September 2008
Abstract:
This article demonstrates the possibility of an alternative approach for risk-adjustment models. In the proposed model the risk characteristics of the beneficiary's health within the same cohort classified by Self-Organizing Map network are highly homogeneous, whereas the numbers of individuals within each cohort remain sufficient to allow further investigation of the causal effect from clustered data. A comparison of different models by the 10-fold cross-validation reveals that the performance improvement in the proposed integration model is both significant and stable across the estimation and validation sampling.
papers.ssrn.com/sol3/papers.cfm?abstract_id=1202445