Re: [scikit-learn] Optimization algorithms in scikit-learn

This is out of the scope of scikit-learn, which is a toolkit meant to be used for easier machine learning. Optimization is a component of machine learning, but not one that is readily-useable by itself. Gaël On Tue, Sep 04, 2018 at 12:45:09PM -0600, Touqir Sajed wrote: > Hi Andreas, > Is there a

Re: [scikit-learn] Optimization algorithms in scikit-learn

Hi Andreas, Is there a particular reason why there is no general purpose optimization module? Most of the optimizers (atleast the first order methods) are general purpose since you just need to feed the gradient. In some special cases, you probably need problem specific formulation for better perf

Re: [scikit-learn] Multi Armed Bandit Algorithms in Scikit-learn

See http://scikit-learn.org/dev/faq.html#what-are-the-inclusion-criteria-for-new-algorithms and http://scikit-learn.org/dev/faq.html#why-is-there-no-support-for-deep-or-reinforcement-learning-will-there-be-support-for-deep-or-reinforcement-learning-in-scikit-learn Bandit algorithms require a fund

Re: [scikit-learn] Optimization algorithms in scikit-learn

Hi Touqir. We don't usually implement general purpose optimizers in scikit-learn, in particular because usually different optimizers apply to different kinds of problems. For linear models we have SAG and SAGA, for neural nets we have adam. I don't think the authors claim to be faster than SAG, so

Re: [scikit-learn] Multi Armed Bandit Algorithms in Scikit-learn

The corrected link : https://www.quora.com/In-what-kind-of-real-life-situations-can-we-use-a-multi-arm-bandit-algorithm ; On Tue, Sep 4,

[scikit-learn] Multi Armed Bandit Algorithms in Scikit-learn

Hi, This email is intended to initiate a discussion on whether it is worth adding Multi-Armed Bandit (MAB) algorithms in Scikit-learn. For those of you who have not heard of MAB algorithms, they are the simplest form of decision-making algorithms applicable whenever data with labels are not given

[scikit-learn] Optimization algorithms in scikit-learn

Hi, I have been looking for stochastic optimization algorithms in scikit-learn that are faster than SGD and so far I have come across Adam and momentum. Are there other methods implemented in scikit-learn? Particularly, the variance reduction methods such as SVRG ( https://papers.nips.cc/paper/493