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What is Understanding Multiclass Classification about?

Multi-class classification involves classifying elements into multiple classes rather than two classes. Examples include classifying news articles, books, and students. Popular algorithms for multi-class classification include k-nearest neighbors, decision trees, naive bayes, random forest, and gradient boosting. Binary classifiers can be adapted for multi-class problems using techniques like one-vs-rest and one-vs-one which break the problem into multiple binary classification problems.

Author

shipukumar009

Language

EN