The objective of this challenge is to develop a machine learning model that for around 10,000 customers in the test set, you are given all but one of the products they own, and are asked to make predictions around which products are most likely to be the missing product., have a look on Zindi.
# 1. run Every single notebook in the folder stack
## after Running those 7 models you will get 35 OOF and 7 main.csv
# 2. run Final_version_Binary_Stacking to get Final_version_Binary_Stacking.csv
# 3. Run finale_version_multiClass_7Models to get finale_version_multiClass_7Models.csv
# 4. Run finale_version_multiClass_stack_3Models to get finale_version_multiClass_stack.csv
# 5. Run Blend_Ronny to get best.csv
# 6. Run best_score to get best_score.csv
To make sure that everything is working smoothly, here is what to expect from above (steps):
# 1. in the stacker folder :
- in notebooks :: RONNY_NEW_Stacker_CNN , RONNY_NEW_Stacker_FFN , RONNY_Stacker_XGBOOST , RONNY_Stacker_LGBM , Please don't miss to restart runtime After Running
this commande << !pip install --upgrade pandas==0.25.3 >> , if you miss to install it , there is an error that will apear later ,
So Please don't miss to Restart your runtime
Look for the team name : ARK
Rank : 5/614
| Name | Zindi ID | Github ID |
|---|---|---|
| Azer KSOURI | @ZRUETASILITU | @Az-Ks |
| Ronny Polle | @drcod | @DrCod |
| Helmi KLAI | @Klai | @Klaimohelmi |