A Framework to Predict the Value of Cryptocurrencies Using the Decision Tree and Regression

Investors are increasingly interested in cryptocurrencies like Bitcoin. In this paper, we investigate how to make accurate Bitcoin price predictions by analysing a number of factors that affect that price. As a first order of business, our research tracks and identifies an ongoing price trend in Bitcoin's day-to-day fluctuations. Data is taken up to the present day, including the opening, closing, and all points in between prices for Bitcoin. We offer a machine learning module that uses the dataset to make price predictions. The purpose of this research is to compare the predictive abilities of several machine learning algorithms for predicting Bitcoin values. Both the decision tree and the regression model are compared to experimental results.