31

**FAQ / Re: Analysis Wizard**

« **on:**September 08, 2014, 09:09:37 »

Hi,

This depends on the domain and the application. It may also be relevant to take a look at AUC of the ROC (which should be at least 0.5). By searching the internet you will be able to find rules of thumb on how to interpret/classify the performance of a classifier based on the AUC of the ROC.

I do not understand this comment. If the performance of the model is not sufficient, then the model should be improved. When building a Bayesian network classifier from data a number of design choices have to be made, e.g., which variables to include, how do discretize numerical variables and which edges should be present in the model. It is impossible to say how you model could be improved without a detailed description of the model and data.

Quote

In the Analysis Wizard, the Error rate for Test Data Accuracy pane of how much is acceptable?

This depends on the domain and the application. It may also be relevant to take a look at AUC of the ROC (which should be at least 0.5). By searching the internet you will be able to find rules of thumb on how to interpret/classify the performance of a classifier based on the AUC of the ROC.

Quote

In section Case table, The probability values 0.5 or less, Large difference between the actual data and test data are available (By multiplying the probabilities of each category for discrete data.), the cause is?what to do to fix it?

I do not understand this comment. If the performance of the model is not sufficient, then the model should be improved. When building a Bayesian network classifier from data a number of design choices have to be made, e.g., which variables to include, how do discretize numerical variables and which edges should be present in the model. It is impossible to say how you model could be improved without a detailed description of the model and data.