Hi there. I tried several methods, using both ML and deep learning. I, however, got the best results using a CNN with ResNet50 with class weights. My lb score never went beyond 0.77. I'd appreciate some feedback regarding where I got it wrong.
Thanks.
Ahmad Wali.
https://colab.research.google.com/drive/1tjf1VEpUKoVnnfh-ykSOivirQvi7nHOa#scrollTo=irtKq_J_3WsX
A few things that I used that I don't see in your code:
- Data augmentation (randomly flip, rotate, adjust brightness/contrast)
- Train with all negative samples. With each epoch I selected a random negative subset equal to the size of the positive samples.
- Remove or handle no-data values. Values <0, typically it was set to -9999 and can cause issues within the CNN. You can remove those samples or fill no-data values with mean valid data.
- Your dropout value seems to be very high.
Thanks a lot. That's really insightful. I didn't notice there were no-data values. I really appreciate it.
It will also be better I think to output raw float probability values rather than int 0 or 1 values.
@backyard baseball In my opinion, it would be more beneficial to output raw float probability values instead of int 0 or 1.