Difference between revisions of "Error correcting output coding"
From Cohen Courses
Jump to navigationJump to searchPastStudents (talk | contribs) (Created page with 'This is a [[category::method]] discussed in [[category::paper]] RelatedPaper::Ditterich and Bakiri, JAIR 1995. == Relevant Papers == {{#ask: UsesMethod::ECOC | ?Add…') |
PastStudents (talk | contribs) |
||
Line 1: | Line 1: | ||
This is a [[category::method]] discussed in [[category::paper]] [[RelatedPaper::Ditterich and Bakiri, JAIR 1995]]. | This is a [[category::method]] discussed in [[category::paper]] [[RelatedPaper::Ditterich and Bakiri, JAIR 1995]]. | ||
− | + | Error Correcting Output Coding (ECOC) converts a m-class supervised learning problem into a n binary problems. | |
− | + | The algorithm assigns each class a unique binary codewords of length n. Then it trains n classifiers to predict each | |
+ | bit in the codewords. The predicted class is the one whose codewords is the closest to the one predicted by the classifier. | ||
Latest revision as of 14:38, 30 November 2010
This is a method discussed in paper Ditterich and Bakiri, JAIR 1995.
Error Correcting Output Coding (ECOC) converts a m-class supervised learning problem into a n binary problems. The algorithm assigns each class a unique binary codewords of length n. Then it trains n classifiers to predict each bit in the codewords. The predicted class is the one whose codewords is the closest to the one predicted by the classifier.