Stock Market Analysis Using Linear Regression and Decision Tree Regression

Abstract

In business, the Stock market or Share market is a more perplexing and sophisticated way to do business. Every business owner wants to reduce the risk and make an immense profit using an effective way. The bank sector, brokerage corporations, small ownerships, all depends on this very body to earn profit and reduce risks. However, using the machine learning algorithm of this paper to predict the future stock price and shuffle by using subsist algorithms and open source libraries to assist in inventing this unsure format of business to a bit more predictable. The proposed system of this paper works in two methods - Linear Regression and Decision Tree Regression. Two models like Linear Regression and Decision Tree Regression are applied for different sizes of a dataset for revealing the stock price forecast prediction accuracy. Moreover, the authors of this paper have revealed some development that could be the club to acquire better validity in these approaches.