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The Magic of Ensembling Models
The magic of ensembling models is that youou get to cancel out the errors of the one model with the other models. That's why it's particularly useful in finance to use many, many models. And numerae has the most. But is there an optimal number? In bringing this collective intelligence together? Does it make a difference to continue to grow this pool of data scientists providing you with models? So interestingly, we give out an example model, which is an extra bose model, if you're familiar with data science usess decision trees. And we give it out as an example model. It beats a lot of users sometimes. Ah, and so that's the magic of