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by wuj
767 days ago
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Time series data are inherently context sensitive, unlike natural languages which follow predictable grammar patterns. The patterns in time series data vary based on context. For example, flight data often show seasonal trends, while electric signals depend on the type of sensor used. There's also data that appear random, like stock data, though firms like Rentech manage to consistently find unlerlying alphas. Training a multivariate time series data would be challenging, but I don't see why not for specific applications. |
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Also, the first realistic approximation of Solomonoff induction we achieve is going to be interesting because it will destroy the stock market.