Karar Ağacı ile Cox karma modeli ve lastik verileri üzerine bir uygulama

Cox hybridmodel with decision tree and an application on data of tires The main purpose in Cox regression method is to create a model to reflect the general status of the data. The effects of the independent variables having an effect on survival time can be measured with this model. However, when the assumption of proportional hazards is not satisfied, Cox regression model is not an appropriate model. Therefore, a hybrid model combining Cox regression with a tree-structured model is created for situations in which assumptions were not satisfied. This mixed model consists of adding to the Cox regression model as a step function of the nodes obtained by decision tree method. In this study, Cox hybrid model with decision tree is used for the first time in data of tires at Kangal Coal Plant in order to determine the variables which are thought to be effective on the survival time of tires. For this data, which do not satisfy proportional hazards assumption, the Cox hybrid model with decision tree is seen to be better than the classical Cox regression model.