Ahh, but are you using one model per target? There really is a ton of things we can try in this comp bc of how different the users are and how much legroom they give us with the datasets. As a data science newbie, I found this to be a pretty awesome comp to explore and keep experimenting. Still 14 days to go!
Wow, trying all CV methods, I still can not get consistent CV/LB score....
How did you made it to 0.89? Only by FE and a realiable CV method?
Yes lot of Engineered features and making sure to avoid all sorts of Target leakage.
Training 10 kfold(shuffle=True) with separate tuned LGBM and sampled dataset for each month that needs predicting is what got me over 0.9.
Thanks Daniel, I will also test it out with my engineered features :). Till now, I have been training with 5 folds only.
Update: Disappointed with the shuffled 10fold performance, didn't help me any boost
Ahh, but are you using one model per target? There really is a ton of things we can try in this comp bc of how different the users are and how much legroom they give us with the datasets. As a data science newbie, I found this to be a pretty awesome comp to explore and keep experimenting. Still 14 days to go!