Russian Federation
Russian Federation
The article discusses the current aspects related to the process of forming a training data sample, which is a key element in the training process of an artificial neural network designed to function as a stock exchange trading BOT. We will try to comprehensively cover all the subtleties and nuances that must be taken into account when preparing this sample in order to ensure maximum efficiency and accuracy in the operation of the trading algorithm. This will allow us to achieve the best results in automating trading operations on the exchange and increase the overall productivity of trading strategies implemented using artificial intelligence. A method is proposed aimed at clustering the training sample data. This method allows you to effectively group similar data according to certain criteria, which, in turn, helps to increase the accuracy and efficiency of training algorithms.
trading bot, training sample, artificial neural network, clustering
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