mql5

Machine learning relies on training data to learn the general behaviour of the market to ultimately make fairly accurate predictions. The chosen learning algorithm has to wade through a carefully selected sample to extract meaningful information. Indicators can be thought of as purveyors of information about the underlying price series they are applied to. Using this premise, entropy can be used to measure how much information is communicated by an indicator. Using steps and tools documented in the book, Testing and Tuning Market Trading Systems (TTMTS) written by Timothy Masters, we will demonstrate how these can be used to evaluate the structure of indicator data.

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