Feature Types

​Feature Types - no permission doc
Discrete 
Numbers 
Categorical
Categorical data are variables that contain label values rather than numeric values.
The number of possible values is often limited to a fixed set.
Categorical variables are often called nominal.
labels, usually discrete values such as gender, country of origin, marital status, high-school graduate
Continuous (the opposite of discrete): real-number values, measured on a continuous scale: height, weight. 

In order to compute a regression, categorical predictors must be re-expressed as numeric: some form of indicator variables (0/1) with a separate indicator for each level of the factor. 
Discrete with many values are often treated as continuous, i.e. zone numbers - > binary

​Variable types: Nominal(weather), ordinal(order var 1,2,3), interval(range), 
Probability
Features
Last modified 1yr ago