Predictive Classification Function

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A predictive classification function is a classification function that is a predictive function.



References

2009

  • (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?s=classifier
    • S: (n) classifier (a person who creates classifications)
    • S: (n) classifier (a word or morpheme used in some languages in certain contexts (such as counting) to indicate the semantic class to which the counted item belongs)


  • http://www.predictionworks.com/glossary/
    • Classifier: 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. See also: Accuracy, Classification Algorithm, Confusion Matrix, Cost-Benefit Matrix, Estimation, Model, and Type I and Type II Errors.

2008

  • Peter L. Rosenbaum, Robert J. Palisano, Doreen J. Bartlett, Barbara E. Galuppi, and Dianne J. Russell. “Development of the gross motor function classification system for cerebral palsy." Developmental Medicine & Child Neurology 50, no. 4 (2008): 249-253.

1998

  • (Kohavi & Provost, 1998) ⇒ Ron Kohavi, and Foster Provost. (1998). “Glossary of Terms.” In: Machine Leanring 30(2-3).
    • Classifier: A mapping from unlabeled instances to (discrete) classes. Classifiers have a form (e.g., decision tree) plus an interpretation procedure (including how to handle unknowns, etc.). Some classifiers also provide probability estimates (scores), which can be thresholded to yield a discrete class decision thereby taking into account a utility function.

1995