Comparison of Fast Learning Large Scale Multi-Class Classification

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Provided by: RWTH Aachen University
Topic: Data Management
Format: PDF
Recent progress in the development of techniques to optimize large scale classification problems has extended the use of multi-class classification. Specifically the use of multi-class classification algorithms, when the dataset is too large to fit into limited memory available of most computers. The most prominent algorithms used today solve the multi-class classification problem through an optimization approach based on coordinate decent. Two of the most recognized algorithms, Vowpal Wabbit and LIBLINEAR LibSVM have emerged as the most consistent options when solving for a multi-class problems.
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