Difference between revisions of "10-601 Bias-Variance"

Revision as of 08:54, 9 October 2013

Bishop: Chap 1, 2 Mitchell: Chap 5, 6 Feature Selection in Microarray Analysis, E.P. Xing, in D.P. Berrar, W. Dubitzky and M. Granzow (Eds.), A Practical Approach to Microarray Data Analysis, Kluwer Academic Publishers, 2003. On Feature Selection: Learning with Exponentially many Irrelevant Features as Training Examples, Andrew Y. Ng. In Proceedings of the Fifteenth International Conference on Machine Learning, 1998.

The battle against overfitting
- Cross validation
- Regularization
- Feature selection

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 [http://curtis.ml.cmu.edu/w/courses/images/2/2e/Lecture11-bv.pdf Slides in PDF]
+=== Readings ===
+Bishop: Chap 1, 2
+Mitchell: Chap 5, 6
+[http://www.cs.cmu.edu/~epxing/papers/Old_papers/feature.pdf Feature Selection in Microarray Analysis], E.P. Xing, in D.P. Berrar, W. Dubitzky and M. Granzow (Eds.), A Practical Approach to Microarray Data Analysis, Kluwer Academic Publishers, 2003.
+[http://ai.stanford.edu/~ang/papers/icml98-fs.pdf On Feature Selection: Learning with Exponentially many Irrelevant Features as Training Examples], Andrew Y. Ng. In Proceedings of the Fifteenth International Conference on Machine Learning, 1998.
+=== Take home message ===
+* Overfitting
+** kNN
+** Regression
+* Bias-variance decomposition
+* Structural risk minimization
+* The battle against overfitting
+** Cross validation
+** Regularization
+** Feature selection