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/>
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