In a problem of an epidemiology dataset, is it desirable to keep the features that have almost constant values? For example, In case of the feature, type_of_residence Large for 97 percent and Small for 2.7 percent of subjects. Is it okay to keep this feature?
My target variable is outcome of patients and this data set is unbalanced. Like oversampling and under sampling techniques in class imbalance problem, is there any process in ML to address other predicting features?
I am not doing feature selection using ML at this point for knowing the importance of this feature. But would like to know is there any general rules regarding keeping or not keeping these kind of features in dataset.