Class Prediction Act
(Redirected from Labeling Act)
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A class prediction act is a prediction act of a classification task (by a classifier).
- AKA: Class-Decisionining Act, Categorization Act.
- Context:
- Act Outcome: a Predicted Class.
- It can be an input to a Classifier Performance Metric.
- It can range from being a Correct Classification Act to being an Incorrect Classification Act (e.g. a false negative).
- Example(s):
- a Tagging Act.
- …
- Counter-Example(s):
- See: Decision Act, Classifier Performance, Cost-Benefit Matrix, Type I Error, Type II Error.
References
2002
- (Gabor Melli, 2002) ⇒ Gabor Melli. (2002). “PredictionWorks' Data Mining Glossary." PredictionWorks.
- Classification/Classifier: The act of labeling a test case into one of a finite number of output classes. A model that classifies is sometimes referred to as a "classifier". Commonly a classifer's performance is measured by its ability to correctly label unseen test cases, that is its "accuracy". Inversely a classifier's performance may be measured by its "error rate". A more detailed insight into a classifier's performance is given by the Confusion Matrix structure because it captures how well the classifier predicts each of the available classes. If a Cost-Benefit Matrix is available then the classifier's performance is measured by the product of the Confusion and Cost-Benefit matrices.