Hi, Ok, then I will continue with the test accuracy in mind.
On Fri, Jun 19, 2015 at 2:01 PM, Nirmal Fernando <[email protected]> wrote: > Hi Thushan, > > Yes, so currently we take a training data fraction as an input from the > user (check the wizard) which splits the dataset to training and test. And > for other algorithms too, Spark generates an accuracy measurement using the > test data predictions vs actual. > > test *accuracy* sounds good as a measurement. > > On Fri, Jun 19, 2015 at 9:19 AM, Thushan Ganegedara <[email protected]> > wrote: > >> Hi all, >> >> Thank you very much for the feedback >> >> One small thing, is there a some sort of accuracy measurement that we can >> show for deep networks? >> >> Yes, there is. Usually the accuracy of the deep network is shown with a >> validation dataset and a test set (i.e. validation error and test error). >> In other words, after training the network, we run an independent test set >> and see how accurate the algorithm is (# of correct results/ # of total >> results) >> >> It seems the test accuracy would fit for the model comparison >> >> On Fri, Jun 19, 2015 at 1:01 PM, Nirmal Fernando <[email protected]> wrote: >> >>> Hi Thushan, >>> >>> Looks good for me too. One small thing, is there a some sort of accuracy >>> measurement that we can show for deep networks? This is required for the >>> model comparison page; >>> https://docs.wso2.com/display/ML100/Model+Comparison >>> >>> On Fri, Jun 19, 2015 at 7:27 AM, Thushan Ganegedara <[email protected]> >>> wrote: >>> >>>> Hi, >>>> >>>> as he configure, can we visualize the deep network ( use some d3 graph >>>> library). >>>> I don't think I understood. Are you asking if we could show the user a >>>> diagram of the network he has specified (like the attached image)? >>>> >>> >>>> Also, after he has trained, can we let him visualize the output of >>>> intermediate layers ( this is a advanced feature, so optional). >>>> Intermediate levels are quite tricky to visualize. Two major issues >>>> with visualizing intermediate layers are, >>>> 1. Intermediate layers are not linear transformations of the input so >>>> the visualized filters of intermediate layers doesn't make much sense (I >>>> tried it, what I saw was completely random pixels) >>>> >>>> 2. It is possible to overcome the above issue with a technique called >>>> activation maximization (we are solving the optimization problem z = >>>> sigmoid(x.W) by keeping W constant and changing x to get the maximum z). >>>> However, this is highly non-convex. So it easily get stuck in local maxima. >>>> Also, this is to costly for large dimensional data (it will work for MNIST >>>> though). >>>> >>>> Thank you >>>> >>>> On Fri, Jun 19, 2015 at 11:50 AM, Srinath Perera <[email protected]> >>>> wrote: >>>> >>>>> Hi Tushan, >>>>> >>>>> OK high level. However, as he configure, can we visualize the deep >>>>> network ( use some d3 graph library). >>>>> >>>>> Also, after he has trained, can we let him visualize the output of >>>>> intermediate layers ( this is a advanced feature, so optional). >>>>> >>>>> --Srinath >>>>> >>>>> On Fri, Jun 19, 2015 at 6:56 AM, Thushan Ganegedara <[email protected]> >>>>> wrote: >>>>> >>>>>> Dear all, >>>>>> >>>>>> Please find the proposed UI changes for the Deep Network Integration >>>>>> attached herewith. >>>>>> >>>>>> Feedback would be highly appreciated. >>>>>> >>>>>> -- >>>>>> Regards, >>>>>> >>>>>> Thushan Ganegedara >>>>>> School of IT >>>>>> University of Sydney, Australia >>>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> ============================ >>>>> Blog: http://srinathsview.blogspot.com twitter:@srinath_perera >>>>> Site: http://people.apache.org/~hemapani/ >>>>> Photos: http://www.flickr.com/photos/hemapani/ >>>>> Phone: 0772360902 >>>>> >>>> >>>> >>>> >>>> -- >>>> Regards, >>>> >>>> Thushan Ganegedara >>>> School of IT >>>> University of Sydney, Australia >>>> >>> >>> >>> >>> -- >>> >>> Thanks & regards, >>> Nirmal >>> >>> Associate Technical Lead - Data Technologies Team, WSO2 Inc. >>> Mobile: +94715779733 >>> Blog: http://nirmalfdo.blogspot.com/ >>> >>> >>> >> >> >> -- >> Regards, >> >> Thushan Ganegedara >> School of IT >> University of Sydney, Australia >> > > > > -- > > Thanks & regards, > Nirmal > > Associate Technical Lead - Data Technologies Team, WSO2 Inc. > Mobile: +94715779733 > Blog: http://nirmalfdo.blogspot.com/ > > > -- Regards, Thushan Ganegedara School of IT University of Sydney, Australia
_______________________________________________ Dev mailing list [email protected] http://wso2.org/cgi-bin/mailman/listinfo/dev
