This question could go here or on S.O. perhaps...
Suppose that your training dataset contains both categorical and continuous data such as this setup:
Animal, breed, sex, age, weight, blood_pressure, annual_cost cat, calico, M, 10, 15 , 100 , 100 cat, tabby, F, 5, 10 , 80 , 200 dog, beagle, M, 3, 30 , 90 , 200 dog, lab, F, 8, 75 , 80 , 100
And the dependent variable to be predicted is the annual vet cost. I'm a bit confused as to the specific techniques available to deal with such a dataset. What are the methods commonly used to deal with datasets that are a mixture of both continuous and categorical data?