The ARGONet model

The ARGONet model is an ensemble approach combining the predictive power of ARGO and Net models. To combine the results of both models, we tested three methods:

First, for a given week, we choose ARGO’s estimate if it leads to the lowest mean prediction error in the previous K weeks (compared to the Net model’s estimate). If this is not true, we choose Net’s estimate. The values of K were inspired by Lu et al. [9] study and verified using cross-validation during the training time period.

A second method consists of calculating the mean value of the estimates produced by the ARGO and Net models for a given week.

In the final method, for a given week, ARGONet’s estimate is built as a linear combination of estimates produced by ARGO and Net. The coefficients are dynamically calculated each week to best predict new ground truth data available each week.