Comparative Analysis of Various Machine Learning Approaches for Bitcoin Price Prediction

被引：0

作者：

Muvvala, Abhishek ^{[1
]}

Chivukula, Rohit ^{[2
]}

Lakshmi, T. Jaya ^{[3
]}

机构：

[1] DXC Technol, Chennai, India

[2] Univ Huddersfield, Sch Comp & Engn, Huddersfield, England

[3] SRM Univ, Dept Comp Sci & Engn, Amaravati, Andhra Pradesh, India

来源：

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ADVANCES IN SIGNAL PROCESSING AND ARTIFICIAL INTELLIGENCE, ASPAI' 2020 | 2020年

关键词：

Machine learning; Regression; Bitcoin price prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Bitcoin is used worldwide for digital payment or simply for investment purposes. Bitcoin price prediction is an interesting research problem in current scenario. In this paper, we have studied the application of machine learning approach in predicting the future price of bitcoin. Many dynamic factors effect Bitcoin prices and accurate predictions form strong base for investment decisions. In this study, we have collected the live data corresponding to bitcoin from quindle.com containing 8 features. Then we have compared the prediction performance of 11 regression algorithms. It is found that Lasso regression with a combination of generalised linear regression outperformed others with an improvement of 9 % accuracy over other regression algorithms.

引用

页码：161 / 164

页数：4

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