Re: A priority of constrains for scipy.optimize.minimize

Change your loss function to a penalized form.

IE:

Instead of minimizing L(x)

s.t.

f_1(x) (necessary constraint)
f_2(x) (nice but not necessary constraint)
....

Do this instead:

Minimize L(x) + \lambda * f_2(x)

s.t.

f_1(x)

where \lambda can be a hyper parameter you can tune to trade off how
important constraint f_2 is relative to loss function quality.

Alternatively: if you are doing minimization on a probability simplex, you
can probably re-parametrize your problem so the only viable solution
automatically satisfies those probabilities.  The most common way is to run
your output through a softmax (
https://en.wikipedia.org/wiki/Softmax_function)


On Tue, Feb 5, 2019 at 9:06 AM <[email protected]> wrote:

> Send SciPy-User mailing list submissions to
>         [email protected]
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         https://mail.python.org/mailman/listinfo/scipy-user
> or, via email, send a message with subject or body 'help' to
>         [email protected]
>
> You can reach the person managing the list at
>         [email protected]
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of SciPy-User digest..."
>
>
> Today's Topics:
>
>    1. A priority of constrains for scipy.optimize.minimize
>       (Jan Hendrik Berlin)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 5 Feb 2019 02:07:35 +0100
> From: Jan Hendrik Berlin <[email protected]>
> To: SciPy-User <[email protected]>
> Subject: [SciPy-User] A priority of constrains for
>         scipy.optimize.minimize
> Message-ID: <[email protected]>
> Content-Type: text/plain; charset=utf-8; format=flowed
>
> Hi,
>
> I am solving a problem with some constrains. At first there is a
> constraint, that the sum of the percentages must be 1. The single
> percentage could be in the range from 0,0 to 1. And this is the main
> constraint. On the other side there are some constrains belonging to
> stuff of the calculation.  It is possible, that this constrains are to
> strong and the solver can't get a solution. In this Case I want to have
> an option to get a solution respecting the first constraint.
>
> Has anybody an idea of a solution? I think there is no option for a
> priority of the constrains.
>
> kind regards
> Jan Hendrik Berlin
>
>
> ------------------------------
>
> Subject: Digest Footer
>
> _______________________________________________
> SciPy-User mailing list
> [email protected]
> https://mail.python.org/mailman/listinfo/scipy-user
>
>
> ------------------------------
>
> End of SciPy-User Digest, Vol 186, Issue 2
> ******************************************
>

_______________________________________________
SciPy-User mailing list
[email protected]
https://mail.python.org/mailman/listinfo/scipy-user