Phaladisailoed, Thearasak and Numnonda, Thanisa (2018) Machine Learning Models Comparison for Bitcoin Price Prediction In: 2018 10th International Conference on Information Technology and Electrical Engineering (ICITEE), 2018-07-24, Kuta.
In recent years, Bitcoin is the most valuable in the cryptocurrency market. However, prices of Bitcoin have highly fluctuated which make them very difficult to predict. Hence, this research aims to discover the most efficient and highest accuracy model to predict Bitcoin prices from various machine learning algorithms. By using 1-minute interval trading data on the Bitcoin exchange website named bitstamp from January 1, 2012 to January 8, 2018, some different regression models with scikit-Iearn and Keras libraries had experimented. The best results showed that the Mean Squared Error (MSE) was as low as 0.00002 and the R-Square (R<sup>2</sup>) was as high as 99.2%.
Item Type:
Conference or Workshop Item (Paper)
Identification Number (DOI):
Deposited by:
ระบบ อัตโนมัติ
Date Deposited:
2021-09-09 23:53:44
Last Modified:
2021-09-17 23:36:25