Quant analytics: Is it possible to improve a predictive model using the data that come after the model is applied?
The new data are supposed to be biased towards the treatment. So how to utilize them in this case? Thanks.
That depends on the model in question. Your initial question is, unfortunately, too general to give a specific answer. You should possibly look into Bayesian Inference or hierarchial Bayesian modelling, with your initial model as your prior.
Yes, consider a Self Organizing Map (SOM). This separates your variables and allows you to find those that have higher correlations between the other variables. “After this model is applied,” you can formulate weights based on these results into a stronger model such as a neural network.
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