I am a student working on creating a model to predict the soybean yield in midwestern states given the parameters of rainfall from April-October and nitrogen consumption. The standard Random Forest and Gradient Boosted Trees models are giving me an R2 score of less than 0.6, so I would like to tune the models to obtain a higher accuracy. Are there any suggestions on what modifications I can make?
Hi, @ellejo! Can you provide any further details on the thread to assist users in helping you find a solution (insert examples like DSS version etc.) Also, can you let us know if you’ve tried any fixes already?This should lead to a quicker response from the community.