Predictive ability of logistic regression, auto-logistic regression and neural network models in empirical land-use change modeling – a case study
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چکیده
منابع مشابه
Comparison of ordinary logistic regression and robust logistic regression models in modeling of pre-diabetes risk factors
Background: Regarding the increased risk of developing type 2 diabetes in pre-diabetic people, identifying pre-diabetes and determining of its risk factors seems so necessary. In this study, it is aimed to compare ordinary logistic regression and robust logistic regression models in modeling pre-diabetes risk factors. Methods: This is a cross-sectional study and conducted on 6460 people, over ...
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Multiple Logistic Regression Just as in OLS regression, logistic models can include more than one predictor. The analysis options are similar to regression. One can choose to select variables, as with a stepwise procedure, or one can enter the predictors simultaneously, or they can be entered in blocks. Variations of the likelihood ratio test can be conducted in which the chi-square test (G) is...
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One of the most important issues always facing banks and financial institutes is the issue of credit risk or the possibility of failure in the fulfillment of obligations by applicants who are receiving credit facilities. The considerable number of banks’ delayed loan payments all around the world shows the importance of this issue and the necessary consideration of this topic. Accordingly...
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Cox’s proportional hazard model or logistic regression model has been the classical mathematical approach to predict transplant results, but artificial neural networks may offer better results. In order to compare both methods, a logistic regression and a neural network model were generated to predict early transplant failure assessed at 90 days. Methods: Medical charts from 701 liver transplan...
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ژورنال
عنوان ژورنال: International Journal of Geographical Information Science
سال: 2011
ISSN: 1365-8816,1362-3087
DOI: 10.1080/13658811003752332