If there’s 23 times more noise, but the opinions are uncorrelated, that’s where the random forest approach comes into its own for a decision tree based on class

If there’s 23 times more noise, but the opinions are uncorrelated, that’s where the random forest approach comes into its own for a decision tree based on classification or regression. Like time series forecasting, and you can choose the weights based on how well the agencies performed in similar situations in the past. “In the multitude of counsellors there is safety” — Prov 11:14