Can I implement 4 different models, one for each field, as long as I compile the results using the format in the sample submission? Or do I need one optimized model that I should apply uniformly across all the fields?
I believe your topic answers the question ha?
You need one optimized model that applys to all the fields.
The aim of this challenge is to create a solution that can be applied to other farms in Senegal, so the final solution needs to be general enough to apply to all fields but still highly accurate.
Hi ZINDI I am still confused, please I need a clarification:
Which one of these two strategies is correct:
- Train on field 1 then predict on field 1
- Train on field 2 then predict on field 2
- Train on field 3 then predict on field 3
- Train on field 4 then predict on field 4
- Train on all 4 fields without mixing information from different fields then predict on all 4 fields