A Review on Machine-Learning Techniques for Estimation of Bitcoin Pricing

Abstract

After the incorporation of machine learning algorithms and regression techniques, this research exhibits the comparison between their individual accuracies. It uses regression models with 80 percent training and 20 percent testing allocation correspondingly with a random state of 10. Various models such as linear regression, lasso regression, ridge regression, polynomial regression, k-nearest neighbour and support vector machine (SVM-Linear) are used for comparison of their accuracies. The obtained dataset contains a variety of parameters which are considered for the comparison and thereby reviewed.