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For the [[binary classification|binary]] case, a common approach is to apply [[Platt scaling]], which learns a [[logistic regression]] model on the scores.<ref name="platt99">{{cite journal |last=Platt |first=John |authorlink=John Platt (computer scientist) |title=Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods |journal=Advances in Large Margin Classifiers |volume=10 |issue=3 |year=1999 |pages=61–74 |url=https://www.researchgate.net/publication/2594015}}</ref>
An alternative method using [[isotonic regression]]<ref>{{Cite book | last1 = Zadrozny | first1 = Bianca| last2 = Elkan | first2 = Charles| doi = 10.1145/775047.775151 | chapter = Transforming classifier scores into accurate multiclass probability estimates | chapter-url = http://www.cs.cornell.edu/courses/cs678/2007sp/ZadroznyElkan.pdf| title = Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '02 | pages = 694–699| year = 2002 | isbn = 978-1-58113-567-1| pmid = | pmc = | id = [[CiteSeerX]]: {{URL|1=citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.7457|2=10.1.1.13.7457}}| citeseerx = 10.1.1.164.8140}}</ref><ref>Rosen, David B.; Burke, Harry B.; Goodman, Philip H. (1996) "Improving Prediction Accuracy Using a Calibration Postprocessor". ''World Congress on Neural Networks'' (WCNN, San Diego, California, September 1996), Erlbaum. "... go through the cases sequentially, enforcing monotonicity. This is the strategy employed by the 'Pool Adjacent Violators' (Barlow et al., 1972) algorithms used to perform monotone regression".</ref> is generally superior to Platt's method when sufficient training data is available.<ref name="Niculescu"/>
In the [[multiclass classification|multiclass]] case, one can use a reduction to binary tasks, followed by univariate calibration with an algorithm as described above and further application of the pairwise coupling algorithm by Hastie and Tibshirani.<ref>{{Cite journal | last1 = Hastie | first1 = Trevor| last2 = Tibshirani | first2 = Robert| doi = 10.1214/aos/1028144844 | title = Classification by pairwise coupling | journal = [[The Annals of Statistics]] | volume = 26 | issue = 2 | pages = 451–471| year = 1998 | pmid = | pmc = | zbl = 0932.62071| id = [[CiteSeerX]]: {{URL|1=citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.46.6032|2=10.1.1.46.6032}}}}</ref>
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