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Old 10-05-2013, 11:39 PM
GB449 GB449 is offline
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Default Data snooping and non-linear transformation

What is the best way to do non-linear transformation but avoid data snooping? The circle example in lecture 18 was a clear case of data snooping. In practice, what information can we safely use to identify candidate non-linear transforms? Should we just try a few (e.g. second order, third order polynomials and pick the best (of course, not sequentially & using information from one transform to influence the next candidate, since that will be data affecting the learning process)).
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