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
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