Categorical Predictor Feature
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A Categorical Predictor Feature is a predictor feature that is a categorical-output function.
- Context:
- It can range from being a Binary Predictor Feature, to being an n-ary Predictor Feature (such as a ternary predictor feature).
- Example(s):
- a Text Token-based Feature, such as:
- a Text Token Part-of-Speech Role Feature, such as [math]\displaystyle{ f }[/math](POS(NNS, “tokens”) ⇒ 1
- a Text Token hasCapitalLetter Feature, such as [math]\displaystyle{ f }[/math](hasCapital("Markov”)) ⇒ 1
- a Text Token Dictionary Match Feature, such as [math]\displaystyle{ f }[/math](equals("Markov”,"Jordan”)) ⇒ 0
- a Text Token Character Pattern Feature, such as [math]\displaystyle{ f }[/math](charPattern("Machine-223") ⇒ "Aaaaaaa-000"
- a Text Token-based Feature, such as:
- Counter-Example(s):
- See: Continuous Independent Variable, Categorical Variable.