Sorry for the delay guys, here's the 2nd place solution. "https://github.com/nikhilmishradevelop/zindi-aws-sansa-hack/", most of the credit still goes to John :D. What worked for me, I guess was using only positive examples instead of both positive and negative examples from the shp file. Initially I saw that my model was predicting mostly negative examples and only a few percentage of positive examples,(less than 5%). Sorry its badly documented, if you have any queries, please ask.
Congrats again, I have a question "why did you clip test preds between 0 and 0.8 ? "
Fares, I did it because log loss is a very unstable metric. Confident wrong predictions are penalized heavily.
Oh I see, thx for the reply!