Albezi method in regression to estimate the tree synthesis model classified and compared to the model Logistics with the application | ||
| Journal of Administration and Economics | ||
| Article 1, Volume 0, Issue 109, November 2018, Pages 335-348 | ||
| Authors | ||
| O.m.d. Omar Abdul Mohsin Ali; MM Suhad Ahmed Ahmed | ||
| Abstract | ||
| The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree model. Having been in this research compare these methods form a model for additive function to some nonparametric function. It was a trade-off between these process models based on the classification accuracy by misclassification error, and estimation accuracy by the root of the mean squares error: RMSE. It was the application on patients with diabetes data for those aged 15 years and below are taken from the sample size (200) was withdrawn from the Children Hospital in Al-Eskan / Baghdad. | ||
| Keywords | ||
| Statistical axis | ||
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