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Recently I attended a presentation by the first author of the following paper who gave us quite a creative and illuminating (kind of meta-)use of random forests in Quant Finance: All that Glitters Is Not Gold: Comparing Backtest and Out-of-Sample Performance on a Large Cohort of Trading Algorithms (March 2016) by Thomas Wiecki, Andrew Campbell, Justin Lent, ...


To be more precise, random forests work by building multiple trees by using sample with replacement from the same training data. Each tree is also built using a random subset of the features (attributes). Pruning is usually done for each tree before its inclusion. Hypothesis values are a result of averaging over all trees. One of the primary uses of ...


try type "GOOG US FLDS" and hit then enter query: DY895 custom formula HELP HELP

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