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摘要
En 中文
in this article, a logistic regression model combined with decision tree for dealing with a significant interaction effect among the explanatory variables is suggested. Decision tree is applied for investigating the interaction among explanatory variables and grouping subjects based on chi(2) value for optimal split. Each group or subjects which is named cluster is determined by optimal split for the interacting explanatory variables, The suggested model incorporates this cluster as an explanatory variable for including significant interaction in the logistic regression model. This model shows better performances in assessment of predictive model than the logistic regression model or decision tree: better ranked classes, increased correct classification rate and R-2, improved Kolmogorov-Smirnov (K-S) statistic, and a better lift. National pension data are applied to this model, and as an application of the Suggested model, strategies for reducing Financial risks in managing and planning for pension financing are illustrated. (C) 2008 Elsevier Ltd. All rights reserved.
Keyword:
The National pension
Survivor's pension
Logistic regression
Decision tree
Predictive model assessment
Classification rate
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IF:
7.5
论文数:
3.0W
被引数:
10.2W
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Predictive factors for long-term sick leave and disability pension among frequent and normal attenders in primary health care over 5 years5年以上初级卫生保健中经常和正常参加人员的长期病假和伤残抚恤金的预测因素.png)
PUBLIC HEALTH.png)
PUBLIC HEALTHIF3.2
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