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The randomized weighted majority algorithm is an algorithm in machine learning theory.It improves the 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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  • The randomized weighted majority algorithm is an algorithm in machine learning theory.It improves the 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. (en)
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  • The randomized weighted majority algorithm is an algorithm in machine learning theory.It improves the 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. (en)
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  • Randomized weighted majority algorithm (en)
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