Bitcoin Price Prediction Using Machine Learning Methods

Abstract

Bitcoin is a new currency that is recognized as a creative payment network. The operating system functions independently of a central structure or bank. Bitcoin is managed by the developed network. Bitcoin's open source code structure allows it to be uncontrolled and uncontrollable by an individual. The use of bitcoin requires virtual wallet. Verification of all payments is secured using public key encryption. Fluctuate in Bitcoin prices at a high rate, making it difficult to predict. For this reason, new cryptology methods related to bitcoin price estimation and security are tried in the literature. In our study, bitcoin price estimation was made by using machine learning methods using KAGGLE Bitcoin Dataset 2010-2019 data set. The methods used are long-short term memory networks, support vector machines, artificial neural networks, Naive Bayes, decision trees and the nearest neighbor algorithm. Obtained accuracy rates are 97.2%, 91.8%, 86.6%, 85%, 81.2% respectively.