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I'm building regression models on four the different but related data set and at the end, I want to test the significance of models. Since my models are built in a different data set, it's not comparable. But there are some hierarchy in my dataset. 1) The output in my main dataset is the sum of the outputs of data set A, B and C 2) The value of feature is the same in all data sets, but all features are NOT present in all data set and some data sets only having a subset of the features of the main data set. 3) The union of the features of the datasets A, B, C are the features of the main data set. So, I want to build a regression model on these data sets seprately and compare the performance and significance of the models togethers.Becuase the dataset are not the exactly the same for all four models, I can not use standard statistics to test the significance of models like AIC, CP-statstics,..... Is there any way to compare the performance of the models ? |
