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The randomized weighted majority algorithm is an algorithm in machine learning theory.It improves the mistake bound of the weighted majority algorithm.
Imagine that every morning before the stock market opens,we get a prediction from each of our "experts" about whether the stock market will go up or down.Our goal is to somehow combine this set of predictions into a single prediction that we then use to make a buy or sell decision for the day.The RWMA gives us a way to do this combination such that our prediction record will benearly as good as that of the single best expert in hindsight.
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