how to optimize multiple classification models why use different metrics can you optimize a classifier model which metric would be used in a good and bad classifier? is there any standard method for defining optimal thresholds and rule sets for classification on separate models? what type of recurrent data is used in classification best method for estimating a classification model which network is best for classifying defining optimal threshold how to improve a classifier based on a model which is an ad hoc approach to classifying why is a classification model used in a deterministic model which is a good model? what is the difference between a good and bad network what is the purpose of a classification model what is the purpose of the bad and good network classification if you have a dataset that includes a good or bad result what is the best model what is the purpose of classification metrics? which metric is best for a good classification model why are the ROC values different for classification