I'm learning ML from Bishop's book. But I don't know that How should I calculate w* in the below picture. enter image description here


Just looked into the book. It was an example of the data that is presented in Fig 1.4. Numpy is a good package to derive the sum of squares fit to the data. This is an optimization problem. Look at the notes section of numpy.polynomial.polynomial.polyfit. I think the data is not given (you can digitize it!). The book is showing some qualitative behavior to give some intuition.

enter image description here

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  • $\begingroup$ I want to understand the problem from the mathematical point of view. $\endgroup$ – Armin Sep 2 '19 at 6:51
  • $\begingroup$ Sure, this is an optimization problem. Have you looked at the notes section of numpy.polynomial.polynomial.polyfit? $\endgroup$ – Mahdiar Sep 2 '19 at 11:44
  • $\begingroup$ Thank you so much. Please, to add the comment to your answer. I accept it. $\endgroup$ – Armin Sep 2 '19 at 14:21

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