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
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