Meta Model Aggregation
Tim and Michael discuss the challenges of improving upon stake weighting in meta model aggregation, highlighting the difficulty in finding a more robust method that avoids overfitting. They explore the impact of payout systems on meta model performance and the evolution of weights over time, emphasizing the importance of adjusting weights towards an optimal meta model.In this clip
From this podcast
Machine Learning Street Talk (MLST)
#105 - Dr. MICHAEL OLIVER [CSO - Numerai]
Related Questions