Great! Please create a Jira. On Tue, Aug 11, 2015 at 12:43 PM, Thushan Ganegedara <thu...@gmail.com> wrote:
> Hi CD, > > No worries. > > On Tue, Aug 11, 2015 at 5:11 PM, CD Athuraliya <chathur...@wso2.com> > wrote: > >> Hi Nirmal, >> >> We will be able to fix this issue. >> >> Thanks Thushan for pointing this out! :) >> >> >> >> On Tue, Aug 11, 2015 at 12:32 PM, Nirmal Fernando <nir...@wso2.com> >> wrote: >> >>> @CD, is this something we could fix? can we list features in the order >>> of the indices? >>> >>> On Tue, Aug 11, 2015 at 12:25 PM, Thushan Ganegedara <thu...@gmail.com> >>> wrote: >>> >>>> Hi, >>>> >>>> I noticed that, in certain cases, the features don't follow the correct >>>> ordering. Any idea why this is happening? >>>> >>>> For example in this image, V10 appears after V1 >>>> >>>> On Tue, Aug 11, 2015 at 12:10 PM, Thushan Ganegedara <thu...@gmail.com> >>>> wrote: >>>> >>>>> Hi all, >>>>> >>>>> After a daunting struggle, I was able to corner the issue with the >>>>> poor accuracy for the specific leaf dataset. The dataset has classes from >>>>> 1 >>>>> to 36. However, there are no classes from 16th - 22nd. i.e. Classes go as >>>>> 1,2,..,14,15,23,24,...,35,36 >>>>> >>>>> Then, while converting these class labels to enums in H-2-O (combined >>>>> with the fact that there's very little data for each class) confuses H-2-O >>>>> and causes it to *assign different enum values for the same classes >>>>> in different datasets*. Which manifest itself as a poor accuracy. >>>>> >>>>> I suspect that there's a mismatch between the labels provided by >>>>> JavaRDD and enums produced by H-2-O as well. I'm looking into this issue >>>>> right now. >>>>> >>>>> Thank you >>>>> >>>>> On Mon, Aug 10, 2015 at 11:16 AM, Thushan Ganegedara <thu...@gmail.com >>>>> > wrote: >>>>> >>>>>> Hi all, >>>>>> >>>>>> I've been testing the new Deeplearning component with few different >>>>>> datasets (mainly leaf dataset) and the leaf dataset seems to be not >>>>>> working >>>>>> as expected for an unknown reason. >>>>>> >>>>>> However, I tested the Deeplearning component extensively with the >>>>>> leaf dataset and identified several potential problems that might be >>>>>> causing the poor accuracy. >>>>>> >>>>>> 1. Need to have higher number of epochs (compared to other datasets) >>>>>> to produce a reasonable accuracy. >>>>>> >>>>>> 2. Too many neurons causing overfitting thereby causing poor accuracy. >>>>>> >>>>>> 3. Some classes have quite closely related features (Especially the >>>>>> latter classes are misclassified often) >>>>>> >>>>>> I was able to get an accuracy of 86% with Logistic Regression L-BFGS. >>>>>> Which is quite reasonable. But I'm having trouble reaching that accuracy >>>>>> with Deeplearning (which should be quite easy). Highest accuracy I >>>>>> reached >>>>>> so far is 71.xx% >>>>>> >>>>>> So I'm still looking for any definite issues causing the poor >>>>>> accuracy. >>>>>> >>>>>> Thank you. >>>>>> >>>>>> >>>>>> -- >>>>>> Regards, >>>>>> >>>>>> Thushan Ganegedara >>>>>> School of IT >>>>>> University of Sydney, Australia >>>>>> >>>>> >>>>> >>>>> >>>>> -- >>>>> Regards, >>>>> >>>>> Thushan Ganegedara >>>>> School of IT >>>>> University of Sydney, Australia >>>>> >>>> >>>> >>>> >>>> -- >>>> Regards, >>>> >>>> Thushan Ganegedara >>>> School of IT >>>> University of Sydney, Australia >>>> >>> >>> >>> >>> -- >>> >>> Thanks & regards, >>> Nirmal >>> >>> Team Lead - WSO2 Machine Learner >>> Associate Technical Lead - Data Technologies Team, WSO2 Inc. >>> Mobile: +94715779733 >>> Blog: http://nirmalfdo.blogspot.com/ >>> >>> >>> >> >> >> -- >> *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/> >> > > > > -- > Regards, > > Thushan Ganegedara > School of IT > University of Sydney, Australia > -- Thanks & regards, Nirmal Team Lead - WSO2 Machine Learner Associate Technical Lead - Data Technologies Team, WSO2 Inc. Mobile: +94715779733 Blog: http://nirmalfdo.blogspot.com/
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