# Feature Types
[**Feature Types**](http://www.biostat.umn.edu/~will/6470stuff/Class09-12/Handout09.pdf) **- 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**](https://en.wikipedia.org/wiki/Nominal_category)**.**
* **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:**](http://www.socialresearchmethods.net/kb/measlevl.php) **Nominal(weather), ordinal(order var 1,2,3), interval(range),**
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