Global minimum, trap

Question

Hi,

how do I avoid being trapped in a local minimum with the regression?

Thanks

Answer 1

Linear régression does not have local minimum issue. It is a convex problem

Comments

Well if your optimisation is polynomial (non-linear) wrt parameters then yeah you can have multiple solution. But in your example, you're polynomial wrt inputs and linear wrt parameters so only one solution with this algorithm.

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What does wrt mean, please?

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With respect to

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To clarify, how should I have indicated my function as multi-dim?
If I write f(para1, para2, para3) you cannot see IMHO you cannot see if it is non-linear.

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No I don't know if it is non-linear, but I assumed it was because 99.9999% of the time in deep learning it is non linear. Otherwise the linear regression will do just fine.