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1_time_series_linear_mapping.R

1_time_series_linear_mapping.R

 
 

2_time_series_pairing.R

2_time_series_pairing.R

 
 

3_dataset_cleaner.R

3_dataset_cleaner.R

 
 

4_tree_booster.R

4_tree_booster.R

 
 

5_linear_ensemble_booster.R

5_linear_ensemble_booster.R

 
 

README.md

README.md

 
 

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Winning solution for Societe Generale predict the crude oil production trend challenge.

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Solution for ENS - Societe Generale Challenge (1st place).

challengedata.ens.fr/en/challenge/25/predict_the_crude_oil_production_trend.html

Topics

competition machine-learning hacking prediction supervised-learning xgboost forecasting ensembles binary-classification panel-data differential-privacy gradient-boosting boosting winning-entry data-leakage machine-learning-competition societe-general classification-tree oild-production-forecast

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