Variance features result in even lower validation accuracy.

Posted: August 4, 2019 at 1:31 pm

The quick variance features were easy to implement, but provided no improvement and performed worse than the previous features. The parameter search resulted in a peak validation accuracy of 64.1% while the best model achieved 66% accuracy on training data and 62.1% on validation data. The following image shows the confusion matrix for validation data. I’m next going to generate colour histograms for the 15000B compositions and see if leads to any improvement.