Main Idea: Find the parameters for a line that partitions a data set.

General Approach (MLIA: p. 84)

Collect Data: any method
Prepare Data: Convert to numeric data if needed.
Analyze: Any method.
Train: Find the optimal coefficients to classify the data.
Use: Given new data, classify it based on the previously classified data.

Pros, Cons, and Data Types

Pros:

Computationally Cheap
Easy to implement
Easy to interpret

Cons:

Succeptible to overfitting
Not always accurate

Data Types:

Numeric Values
Nominal Values

Sidebar on Nominal Values

Nominal Values are data that you can determine to be equivalent to other data or belonging to a set of data, but no ordering or other numeric calculations are possible.

Dichotomous: Belongs to one of two groups
Non-Dichotomous: Belongs to one of multiple groups

Nominal Values are usually summarized using frequencies or percentages (and sometimes summarized by mode).
Column (bar) charts are the best form of graphical representation (along with pie charts)
These are also called categorical or qualitative values