In this article, we explore a feature selection algorithm introduced in the paper 'Local Feature Selection for Data Classification' by Narges Armanfard, James P. Reilly, and Majid Komeili. This method aims to identify predictive features that are often overlooked by traditional selection techniques due to their limited global utility. We will begin with a general overview of the algorithm, followed by its implementation in Python to create classifier models suitable for export to MetaTrader ...
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