Naive Bayesian models
Hi,
As I understand it, the weight given to a descriptor in a naive Bayesian model is proportional to the enrichment of that descriptor in the "active" or "good" set compared with the "bad" or "inactive" set. I would like to know how descriptors with only a very few instances in the training set are treated. With the approach described, you would end up with certainties one way or the other often (or in the extreme case of only one instance, all the time). Are these simply discarded?
thanks for any enlightenment,
Andy
As I understand it, the weight given to a descriptor in a naive Bayesian model is proportional to the enrichment of that descriptor in the "active" or "good" set compared with the "bad" or "inactive" set. I would like to know how descriptors with only a very few instances in the training set are treated. With the approach described, you would end up with certainties one way or the other often (or in the extreme case of only one instance, all the time). Are these simply discarded?
thanks for any enlightenment,
Andy