Prediction of stock price is very challenging task due to dynamic changes value of company stock. The successfully stock prediction helps to profit the company otherwise face the problem of loss. This paper presents the analytical study of various data mining based predictive models to predict the stock in financial domain and find the most consistent prediction model among them. In Stock Market, Data mining play very important role to analysis of data. Data mining techniques can be applied on past and present financial data to generate pattern and decision making. In this paper, we have used predictive techniques like Decision Tree (DT), Random Forest(RF), Support Vector Machine (SVM), Random Tree(RT) and Multilayer Perceptron (MLP) for analysis and perdition of stock market. We have used Bombay Stock Exchange (BSE) data set to analysis of stock market prediction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.