The 2017 AI Challenge

Evaluation Criteria

The challenge is to identify patterns in the data that identify elite experimental varieties and expose the non-elite varieties prior to commercialization. Entries will be judged by the clarity of the solution, the technical strength of the methodology, the uniqueness of the approach, and the degree to which the evaluation data support your conclusions.

(40%) Scientific rigor of the solution, as shown and explained in an accompanying paper (up to 20 pages in length)

(40%) Effectiveness of the approach in identifying the best varieties for the test years (submitted in codalab.org)

(20%) Transparency, interpretation, and self-documentation of models