CSAIL Event Calendar: Previous Series
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Improving multiclass text classification with the Support Vector Machine Speaker: Jason Rennie , Machine Learning Group - MIT AI Laboratory We compare Naive Bayes and Support Vector Machines on the task of multiclass text classification. Using a variety of approaches to combine the underlying binary classifiers, we find that SVMs substantially outperform Naive Bayes. We present full multiclass results on two well-known text data sets, including the lowest error to date on both data sets. We show that the SVM's lower multiclass error is a result of its improved binary performance. Furthermore, we demonstrate and explore the surprising result that one-vs-all classification performs favorably compared to other approaches even though it has no error-correcting properties. This project is joint work with Ryan Rifkin See other events that are part of CSAIL Student Seminar Fall 2001 |
