Criteria and Methods of Evaluating Models
vPrediction ability
vComplexity of compounds used in developing and testing models
vDiversity of compounds used in developing and testing models
vReliability of each parameter (how many and how well data were used in obtaining each parameter)
vSimilarity analysis
The major problem in model evaluations is that very little attention is paid on the prediction abilities of models. The following factors have been considered in our evaluating and selecting of models for TIIS.
What are the criteria to judge a model, to say this one is good and that is not good? How to understand functions of models? In this aspect, big problems exist. There are very few articles in discussing model evaluations.