[Scikit-learn-general] Neural networks for regression?

Dear all, I am not entirely sure whether this is the best place to post this, and please do excuse me if this is not the perfect list for this question. Is there any python packages for neural networks for regression (instead of classification)? Any help would be appreciated. Thanks! -Shawn --

[Scikit-learn-general] Colors of hyperplane plot

Hello, We have a very closely related example to the multiclass iris example: -- Put Bad Developers to Shame Dominate Development with Jenkins Continuous Integration Continuously Automate Build, Test & Deployment Start a

Re: [Scikit-learn-general] Colors of hyperplane plot

Sorry, prematurely sent: We have a very closely related example to the multiclass iris SGD example: http://scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html For our intents and purposes, it would be really helpful if we could change the blue region to magenta. Our other imag

Re: [Scikit-learn-general] Neural networks for regression?

Two libraries[1,2] come to mind that can additionally support accelerators through opencl. Just take note that it can take a bit to familiarize yourself with pylearn2, especially because they seem adamant in doing everything through yaml scripts. [1] -- https://github.com/lmjohns3/theano-nets (see

Re: [Scikit-learn-general] Colors of hyperplane plot

I think what you're looking for is the "cmap" parameter on the pylab calls. See [1] for more info about matplotlib color schemes. [1] -- http://wiki.scipy.org/Cookbook/Matplotlib/Show_colormaps 2014-04-07 11:33 GMT-05:00 Adam Hughes : > Sorry, prematurely sent: > > We have a very closely related

Re: [Scikit-learn-general] Colors of hyperplane plot

So defining my own colormap I presume would be the best solution. On Mon, Apr 7, 2014 at 12:53 PM, Ralf Gunter wrote: > I think what you're looking for is the "cmap" parameter on the pylab > calls. See [1] for more info about matplotlib color schemes. > > [1] -- http://wiki.scipy.org/Cookbook/M

Re: [Scikit-learn-general] Neural networks for regression?

You can also use the python interface to pylearn2, rather than the yaml. If you are interested in examples of the python interface for pylearn2, I have some examples (I greatly prefer the python interface, but to each their own): https://github.com/kastnerkyle/pylearn2-practice/blob/master/cifar10

Re: [Scikit-learn-general] Neural networks for regression?

Also, I think pylearn2 and theano-nets only support CUDA cards (Nvidia), since Teahno only supports CUDA or CPU to my knowledge. There is some discussion of supporting an OpenCL backend ( https://groups.google.com/forum/#!msg/theano-dev/NhRUhWA6xzo/lYrIIOlw4D8J), but I don't know whether that work

Re: [Scikit-learn-general] Neural networks for regression?

Ah, my apologies, I vaguely remembered reading about opencl somewhere in the theano docs... I stand corrected. 2014-04-07 14:42 GMT-05:00 Kyle Kastner : > Also, I think pylearn2 and theano-nets only support CUDA cards (Nvidia), > since Teahno only supports CUDA or CPU to my knowledge. There is so

[Scikit-learn-general] Memory error for decision tree with 66k features, using scikit python packages

Hi Team, > > Kindly help me in the following memory problem and to continue with the research. > > Problem Statement > > I am using a document of 160 lines and ~66k features. I am using the bag of words approach to build a decision tree. Following code is working fine for 1000 line document. B

Re: [Scikit-learn-general] Memory error for decision tree with 66k features, using scikit python packages

In order to use Decision Trees, you'll have to reduce the number of features, by using feature selection: http://scikit-learn.org/stable/modules/feature_selection.html You can also use a classifier that handles sparse matrices, such as Naive Bayes: http://scikit-learn.org/stable/modules/naive_baye