Machine Learning the Cryptocurrency Market - CORE Reader
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Method 3:The LSTM has three parameters: The number of epochs, or complete passes throughthe dataset during the training phase; the number of neurons in the neural network, and the lengthof the windoww. his procedure is repeated for values oftiincluded between January 1, 2016 and Apr
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- Method 3:The LSTM has three parameters: The number of epochs, or complete passes throughthe dataset during the training phase; the number of neurons in the neural network, and the lengthof the windoww.
- his procedure is repeated for values oftiincluded between January 1, 2016 and April 24,2018
- The success of machine learning techniques for stock markets prediction [36–42], suggests that thesemethods could be effective also in predicting cryptocurrencies prices.
- ince 2017, over 170 hedge funds specialised incryptocurrencies have emerged and bitcoin futures have been launched to address institutional demandfor trading and hedging Bitcoin
- Here, we test the performance of three models in predicting daily cryptocurrency price for 1,681currencies.
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