Depends on your feature extractor. If you have a feature that measures similarity to previously-seen films, then yes. Otherwise, no. If you only have features measuring what each film's about, and people like novel films, then you'll get conservative predictions, but that's not really the same as learning that novelty is good.
Thanks. Now I'm trying to learn a bit about (exponential) moving averages. I know moving averages are used in machine learning, but I've also come across them in stock market investing where they are regarded with derision. Can someone explain what their utility is, and how they can be useful when they aren't in trading? If my financial knowledge is correct, moving averages only indicative profitable moves when there are linear dependencies between fundamental variables and the stocks price. This is true both empirically and is what most technical analysts...
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