Factor Analysis
In general, a factor is defined as an element contributing to a result. Factor Analysis is a method to derive new variable factors that relate to a set of sampled variables.
Processes, Inputs, and Outputs
There are a number of processes, inputs, and outputs surrounding Factor Analysis. In total, they can be seen as an iterative loop of refinement to achieve optimal Factor selection.
Items
Items come from a group of data under consideration. Examples of types of Items include:
customers of a business
buyers of a product
voters in an election
patients with an illness
Variable Selection
Variable Selection is the process of determining which Variables are pertinent to training and using a given Machine Learning model.
Variables
Variables are aspects of items. Examples include:
age
income
location
family size
Factor Analysis
Factor Analysis is the process of deriving new variable factors that relate to a set of sampled Variables. An example of this process is Principal Component Analysis.
Factors
Factors are measures derived from Variables. Examples include:
averages
groups (such as using income ranges instead of exact numbers)
ranges (such as date ranges instead of exact dates)
Variable Analysis
Variable Analysis is the process of measuring the Variance related to variables.
Variance Measure
Variance is a measure of the Deviation of variables around a mean value.
The Variance measure can be fed back into Variable Selection and Factor Analysis for iterative rounds of refining result.