February 25th 2010
Some weeks ago, the first release of the optimization scikit was done. I’d like to expose here the internal structure and the way the implementation was thought.
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Loading ...February 2nd 2010
I’m pleased to announce the first release of one of my projects. This scikits is based on a generic framework that can support unconstrained cost function minimization. It is based on a separation principle and is also completely object oriented.
Several optimizers are available:
The usual criterias can be used:
Different direction searches are available:
Finally several line searches (1D minimization) were coded:
Additional helper classes can be used:
Although it is the 0.1 version, the code is quite stable and is used in the learn scikit.
The package can be easy-installed or can be found on PyPI.
Several tutorials are available or will be available on the future at the following locations:
(1 votes, average: 5.00 out of 5) Loading ...December 22nd 2009
Some months ago, I’ve finished my manifold learning posts serie. As support for the manifold learning toolkit, I’ve also developed an optimization framework, which I’ll be blogging about, starting now.
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