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What is L02 OutlierRejection about?

The document discusses outlier rejection in linear regression, covering concepts like pseudo-inverse, Chebyshev inequality, and regression diagnostics. It introduces methods such as Iteratively Reweighted Least Squares (IRLS) and RANSAC for effectively identifying and removing outliers from datasets. The document emphasizes the importance of these techniques in improving the accuracy of regression models.

Author

Debottam Ghosh

Language

EN