Probabilistic Classification Function
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A Probabilistic Classification Function is a predictive classification function that is a discrete probability function.
- AKA: Probabilistic Classifier, Trained Classifier, Induced Classifier, Learned Classifier.
- Context:
- It can associate a Confidence Measure with its Output.
- It range from being a Heuristic Probabilistic Classifier to being a Trained Probabilistic Classifier (though supervised classification).
- Example(s):
- a Bloom Filter.
- a Probabilistic Decision Tree.
- a Logistic Model.
- one that predicts a Random Experiment Outcome for a Categorical Random Experiment.
- Counter-Example(s):
- See: Model-based Supervised Classification Algorithm.