@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/
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