How can I evaluate data mining model? I will evaluate classification models I made. That's logistic regression and decision tress. 
1. What I use standards for comparison?
2. Suppose model selection's standard is ASE. One is high ASE of training data, low ASE of test data, and the other is ASE of training data is low and ASE of test data is high.. If you select a model, which models do you choose?
Accuracy (for classification problems)
Precision
Recall
F1 Score
AUC-ROC, particularly for imbalanced datasets 


Good performance on the training set and bad performance on the test set is due to overfitting. So you should try to find ways to tackle overfitting, such as regularization of parameters, parameter tuning using cross-validation etc...