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
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