(Machine|Statistical) Learning - (Target|Learned|Outcome|Dependent|Response) (Attribute|Variable) (Y|DV)
1 - About
There is two type of outcome variables:
- <math>Y</math>: the original score collected
- the characteristics of the group (such as name)
- and/of the experimentation (such as the steps: before, after).
The target attribute is also called:
- Outcome measurement (Y)
- Dependent variable (DV),
- Response. (It's a statistic term when groups respond to a treatment)
- Explained variable
- Experimental variable
- Output variable
- Criterion Variable
- Unobserved variable
When the target attribute is:
In the test data, it will contain values with known outcomes in order to measure the performance of the model.
Clustering, feature extraction, association, and anomaly detection models do not use a target because they are unsupervised function.