Bitcoin Price Prediction with Random Forest Technique using Python

Abstract

This study applies a Random Forest technique to analyze the Bitcoin fluctuations from January
2019 to December 2020. A Random Forest model, which attributes the right currency margin in
forecasting, was designed using Python. The prices fluctuations were examined by various
measures such as the root mean square error (RMSE), the mean absolute error (MAE), the mean
absolute percentage error (MAPE), and R2. The results show that this technique can forecast trends
in Bitcoin and cryptocurrencies.