Machine Learning

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Revision as of 11:12, 10 November 2019 by David (talk | contribs) (Replaced content with "Machine Learning ==Loss functions== ===(Mean) Squared Error=== The squared error is:<br> <math>J(\theta) = \sum|h_{\theta}(x^{(i)}) - y^{(i)}|^2</math><br> If our model i...")
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Machine Learning

Loss functions

(Mean) Squared Error

The squared error is:

If our model is linear regression then this is convex.

Proof


so the hessian is positive semi-definite