结合逻辑回归和神经网络来创建预测模型。
Combining logistic regression and neural networks to create predictive models.
作者信息
Spackman K A
机构信息
Biomedical Information Communication Center, Oregon Health Sciences University, Portland.
出版信息
Proc Annu Symp Comput Appl Med Care. 1992:456-9.
Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building with neural networks.
神经网络在医学和其他领域正被广泛用于根据数据创建预测模型。与神经网络最为相似的统计方法是逻辑回归。本文概述了神经网络和逻辑回归在某些方面的相似之处，展示了如何通过对逻辑回归进行微小修改来用于神经网络模型的训练，并说明了这种修改在神经网络变量选择和预测模型构建中的应用。
Zotero 插件