This competition was our first as a team and a really tough one. Our solution had a few features, I think it wasn't more than 40. We dropped a lot of features which contribute to overfitting especially the angles(solar and sensor), The average pm2.5 reading was a very useful feature from the feature importance plot. We also used the dry&wet season feature. We had a score of 12.20 but unfortunately we didn't select it before the competition ended but the score we chose earned us the 3rd position. Thank you Zindi.
Team Arrow
Bro that's amazing. 12.20 from just 40 features. Unbelievable. Well done guys well done 👏👏👏
I will check that again but I know it was less than 50
Nice. And by average pm2_5 you mean mean target encoding?
What cv did you guys use ?
We just held out the last 20 days when we sorted by date.
Amazing work!
what did you use for feature selection?
congratulations guys!
Hey @NIRAN . I have been trying to follow your approach and it's really interesting. You said average pm2_5 really helped you guys. How did you calculate that ? Given that in the test we never had pm2_5?
By avg pm2.5, I meant rolling mean of 180 days and took lags of
Nice