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),