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In scikit-learn we have different methods to deal with multi-classification problems, below are some of the meta estimators used

a. OneVsRestClassifier and OneVsOneClassifier which are used for Multiclass classification problem

b. MultiOutputClassifier and ClassifierChain which are used for Multilabel (Multioutput) classification problem

I went through the docs, but I'm unable to understand how these techniques are applied mathematically (or algorithmically/logically)

I would be a great help if anyone would help in this matter

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