Congratulation, Nikhil ! Thanks for sharing ur solution.

Congratulations and Thanks for the solution

Hi Nikhil,

Congratulation for the winning. Can I ask you a favour for you and other top two solutions, if you don't mind could you comment your line of codes or just state objectives on some blocks of codes. This will help most of us to closely and easily follow up your code.

I appreciate and thank you for sharing with us.

i have some questions please, did you use a gridsearch firstly ??

and can you explain you feature engineering ?

i have some questions please, did you use a gridsearch firstly ??

and can you explain you feature engineering ?

Please why do you use train data in valid_sets with simple test data ???

Hello @devnikmishra, in your code i noticed you did-

for i in range(1, 20): df[f'prev_target_{i}'] = df.sort_values(by='Date')[TARGET_COL].fillna(method='ffill').shift(i).sort_index() df[f'next_target_{i}'] = df.sort_values(by='Date')[TARGET_COL].fillna(method='bfill').shift(-i).sort_index()

yeah so this is to get previous and next target yeah but the test set does not have target column so how did use those features in making preditions please explain what you did here Thanks

and this also

for i in tqdm_notebook(range(1, 15)): df[f'magic_{i}'] = df.sort_values(by='Date')[TARGET_COL].shift(i).expanding().mean().fillna(method='ffill').sort_index() df[f'magic2_{i}'] = df.sort_values(by='Date')[TARGET_COL].shift(-i).expanding().mean().fillna(method='bfill').sort_index()

please i'ld like ur explanation