Hi, Yes, I'm alright with the idea of having the review this week.
On Mon, Jul 27, 2015 at 11:27 AM, Nirmal Fernando <[email protected]> wrote: > Thanks Thushan for the update. > > On Mon, Jul 27, 2015 at 6:01 AM, Thushan Ganegedara <[email protected]> > wrote: > >> Hi all, >> >> I'm doing some tests with several datasets and most of them seemed to be >> working fine. Somehow, I stumbled upon the leaf dataset ( >> https://archive.ics.uci.edu/ml/datasets/Leaf), which does not seem to be >> working well for. However, the dataset works fine with other algorithms >> (e.g. Logistic Regression L-BFGS) Therefore, I suspect this is due to some >> sort of malformed data format. I'm right now looking into that. >> >> Furthermore, I am thinking of starting with the D3 visualization on the >> parameter setting stage. Should we be moving forward with that idea? >> > +1 > >> >> Finally, I would like to remind that, we haven't decided a date for code >> review. Should we do that? >> > > Yes, let's have it this week, if you are ok. > >> >> Thank you >> >> On Wed, Jul 22, 2015 at 11:13 PM, Thushan Ganegedara <[email protected]> >> wrote: >> >>> Hi, >>> >>> Apologies about the late reply. >>> >>> Notes of the Demonstration >>> >>> Time duration: approximately 30 mins >>> >>> The demonstration was to demonstrate the implemented deeplearning >>> feature of WSO2-ML. The demo started first explaining the dataset used >>> (i.e. MNIST). The dataset is a CSV file with approximately 30000 rows and >>> 784 features. >>> >>> Next the dataset was loaded to WSO2-ml. Here a concern was raised >>> regarding selecting the type of data in the Preprocessing Phase (i.e. >>> Categorical vs Numerical) The suggestion was that there should be a UI >>> feature to change the data type for all the variables at once (very useful >>> for large amounts of features). >>> >>> Next the deeplearning algorithm for MNIST dataset was demonstrated and >>> was able to achieve an appx 95% accuracy. Regarding the deeplearning >>> algorithms, H-2-O doesn't seem to have different deeplearning algorithms at >>> the moment, but a general deep network + classifier (probably autoencoder). >>> So the idea was to ask H-2-O team whether they are planning to implement >>> different networks in the future. >>> >>> Also, it was suggested to add a visualization feature in parameter >>> setting stage to provide a summarized visualization of the network to the >>> user. >>> >>> Furthermore, another suggestion was to test the deep network on real >>> world datasets and see how it performs. For this datasets from Kaggle will >>> be used. >>> >>> >>> About progress. >>> >>> I'm currently testing the algorithm against different datasets. and I'll >>> provide a detailed report on that in the recent future. >>> >>> Thank you >>> >>> >>> >>> On Wed, Jul 22, 2015 at 2:00 PM, Nirmal Fernando <[email protected]> >>> wrote: >>> >>>> @Thushan how are you progressing? Could you please send the notes of >>>> our last review? >>>> >>>> On Thu, Jul 16, 2015 at 10:43 AM, CD Athuraliya <[email protected]> >>>> wrote: >>>> >>>>> >>>>> >>>>> On Mon, Jul 13, 2015 at 11:12 AM, Thushan Ganegedara <[email protected] >>>>> > wrote: >>>>> >>>>>> Hello CD, >>>>>> >>>>>> Yes, it seems to be working fine now. But why does it show the axes >>>>>> in meters? Is this a d3 specific thing? >>>>>> >>>>> >>>>> I think *m* stands for *Milli* here. >>>>> >>>>>> >>>>>> On Mon, Jul 13, 2015 at 3:17 PM, Thushan Ganegedara <[email protected] >>>>>> > wrote: >>>>>> >>>>>>> Hi all, >>>>>>> >>>>>>> Thank you very much for pointing out. I'll get the latest update and >>>>>>> see. >>>>>>> >>>>>>> On Mon, Jul 13, 2015 at 3:03 PM, CD Athuraliya <[email protected]> >>>>>>> wrote: >>>>>>> >>>>>>>> Hi Thushan, >>>>>>>> >>>>>>>> That method has been updated. Please get the latest. You might have >>>>>>>> to define your own case depending on predicted values. >>>>>>>> >>>>>>>> CD Athuraliya >>>>>>>> Sent from my mobile device >>>>>>>> On Jul 13, 2015 10:24 AM, "Nirmal Fernando" <[email protected]> >>>>>>>> wrote: >>>>>>>> >>>>>>>>> Great work Thushan! On the UI issues, @CD could help you. AFAIK >>>>>>>>> actual keeps the pointer to the actual label and predicted is the >>>>>>>>> probability and predictedLabel is after rounding it using a threshold. >>>>>>>>> >>>>>>>>> On Mon, Jul 13, 2015 at 7:14 AM, Thushan Ganegedara < >>>>>>>>> [email protected]> wrote: >>>>>>>>> >>>>>>>>>> Hi all, >>>>>>>>>> >>>>>>>>>> I have integrated H-2-O deeplearning to WSO2-ml successfully. >>>>>>>>>> Following are the stats on 2 tests conducted (screenshots attached). >>>>>>>>>> >>>>>>>>>> Iris dataset - 93.62% Accuracy >>>>>>>>>> MNIST (Small) dataset - 94.94% Accuracy >>>>>>>>>> >>>>>>>>>> However, there were few unusual issues that I had to spend lot of >>>>>>>>>> time to identify. >>>>>>>>>> >>>>>>>>>> *FrameSplitter does not work for any value other than 0.5. Any >>>>>>>>>> value other than 0.5, the following error is returned* >>>>>>>>>> (Frame splitter is used to split trainingData to train and valid >>>>>>>>>> sets) >>>>>>>>>> barrier onExCompletion for >>>>>>>>>> hex.deeplearning.DeepLearning$DeepLearningDriver@25e994ae >>>>>>>>>> java.lang.RuntimeException: java.lang.RuntimeException: >>>>>>>>>> java.lang.NullPointerException >>>>>>>>>> at >>>>>>>>>> hex.deeplearning.DeepLearning$DeepLearningDriver.trainModel(DeepLearning.java:382) >>>>>>>>>> >>>>>>>>>> *DeepLearningModel.score(double[] vec) method doesn't work. * >>>>>>>>>> The predictions obtained with score(Frame f) and score(double[] >>>>>>>>>> v) is shown below. >>>>>>>>>> >>>>>>>>>> *Actual, score(Frame f), score(double[] v)* >>>>>>>>>> 0.0, 0.0, 1.0 >>>>>>>>>> 1.0, 1.0, 2.0 >>>>>>>>>> 2.0, 2.0, 2.0 >>>>>>>>>> 2.0, 1.0, 2.0 >>>>>>>>>> 1.0, 1.0, 2.0 >>>>>>>>>> >>>>>>>>>> As you can see, score(double[] v) is quite poor. >>>>>>>>>> >>>>>>>>>> After fixing above issues, everything seems to be working fine at >>>>>>>>>> the moment. >>>>>>>>>> >>>>>>>>>> However, the I've a concern regarding the following method in >>>>>>>>>> view-model.jag -> function >>>>>>>>>> drawPredictedVsActualChart(testResultDataPointsSample) >>>>>>>>>> >>>>>>>>>> var actual = >>>>>>>>>> testResultDataPointsSample[i].predictedVsActual.actual; >>>>>>>>>> var predicted = >>>>>>>>>> testResultDataPointsSample[i].predictedVsActual.predicted; >>>>>>>>>> var labeledPredicted = labelPredicted(predicted, 0.5); >>>>>>>>>> >>>>>>>>>> if(actual == labeledPredicted) { >>>>>>>>>> predictedVsActualPoint[2] = 'Correct'; >>>>>>>>>> } >>>>>>>>>> else { >>>>>>>>>> predictedVsActualPoint[2] = 'Incorrect'; >>>>>>>>>> } >>>>>>>>>> >>>>>>>>>> why does it compare the *actual and labeledPredicted* where it >>>>>>>>>> should be comparing *actual and predicted*? >>>>>>>>>> >>>>>>>>>> Also, the *Actual vs Predicted graph for MNIST show the axis in >>>>>>>>>> "Meters" *(mnist.png) which doesn't make sense. I'm still >>>>>>>>>> looking into this. >>>>>>>>>> >>>>>>>>>> Thank you >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> -- >>>>>>>>>> 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 >>>>>>> >>>>>> >>>>>> >>>>>> >>>>>> -- >>>>>> Regards, >>>>>> >>>>>> Thushan Ganegedara >>>>>> School of IT >>>>>> University of Sydney, Australia >>>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> *CD Athuraliya* >>>>> Software Engineer >>>>> WSO2, Inc. >>>>> lean . enterprise . middleware >>>>> Mobile: +94 716288847 <94716288847> >>>>> LinkedIn <http://lk.linkedin.com/in/cdathuraliya> | Twitter >>>>> <https://twitter.com/cdathuraliya> | Blog >>>>> <http://cdathuraliya.tumblr.com/> >>>>> >>>> >>>> >>>> >>>> -- >>>> >>>> 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 >>> >> >> >> >> -- >> 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
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