Re: [Scikit-learn-general] Artificial Neural Networks
Issam Laradji implemented a multilayer perceptron and extreme learning machines for last year's GSoC. Both are awaiting final reviews before being merged. They should be functional and can be found in the Issue Tracker. On 7 April 2015 at 21:09, Vlad Ionescu ionescu.vl...@gmail.com wrote: Hello, I was wondering why there isn't a classic neural network implementation in scikit-learn (a multilayer perceptron). This could have varying levels of complexity: it could be hardcoded to just one hidden layer, allowing one to specify the type of neurons in it (sigmoid, tanh, rectified linear etc.), the learning rate and values for weight decay and momentum. It could also be made to accept multiple hidden layers, with the ability to specify the number of neurons and their type for each one. Has this been considered before but no one has gotten around to it? Would it be of interest for you? There are of course more sophisticated methods that would be nice to have as well. I'm only asking about the basic type because that is what I currently would be willing to help with, but it would be great if more were under consideration. -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
Re: [Scikit-learn-general] Artificial Neural Networks
I do not know if this can be useful but I wrote a simple Single layer neural network script based on pylearn2 https://justpaste.it/kdyg On Tue, Apr 7, 2015 at 1:16 PM, Joel Nothman joel.noth...@gmail.com wrote: Issam Laradji implemented a multilayer perceptron and extreme learning machines for last year's GSoC. Both are awaiting final reviews before being merged. They should be functional and can be found in the Issue Tracker. On 7 April 2015 at 21:09, Vlad Ionescu ionescu.vl...@gmail.com wrote: Hello, I was wondering why there isn't a classic neural network implementation in scikit-learn (a multilayer perceptron). This could have varying levels of complexity: it could be hardcoded to just one hidden layer, allowing one to specify the type of neurons in it (sigmoid, tanh, rectified linear etc.), the learning rate and values for weight decay and momentum. It could also be made to accept multiple hidden layers, with the ability to specify the number of neurons and their type for each one. Has this been considered before but no one has gotten around to it? Would it be of interest for you? There are of course more sophisticated methods that would be nice to have as well. I'm only asking about the basic type because that is what I currently would be willing to help with, but it would be great if more were under consideration. -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
Re: [Scikit-learn-general] Artificial Neural Networks
I have a simple nesterov momentum in Theano modified from some code Yann Dauphin had, here: https://github.com/kastnerkyle/ift6266h15/blob/master/normalized_convnet.py#L164 On Tue, Apr 7, 2015 at 10:44 AM, Andreas Mueller t3k...@gmail.com wrote: Actually Olivier and me added some things to the MLP since then, and we still want to add early stopping and Nesterov's momentum before merging it: https://github.com/scikit-learn/scikit-learn/pull/3939 On 04/07/2015 07:16 AM, Joel Nothman wrote: Issam Laradji implemented a multilayer perceptron and extreme learning machines for last year's GSoC. Both are awaiting final reviews before being merged. They should be functional and can be found in the Issue Tracker. On 7 April 2015 at 21:09, Vlad Ionescu ionescu.vl...@gmail.com wrote: Hello, I was wondering why there isn't a classic neural network implementation in scikit-learn (a multilayer perceptron). This could have varying levels of complexity: it could be hardcoded to just one hidden layer, allowing one to specify the type of neurons in it (sigmoid, tanh, rectified linear etc.), the learning rate and values for weight decay and momentum. It could also be made to accept multiple hidden layers, with the ability to specify the number of neurons and their type for each one. Has this been considered before but no one has gotten around to it? Would it be of interest for you? There are of course more sophisticated methods that would be nice to have as well. I'm only asking about the basic type because that is what I currently would be willing to help with, but it would be great if more were under consideration. -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general -- BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15utm_medium=emailutm_campaign=VA_SF ___ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
