An Improved Random Forest Algorithm For Effective Stock Market Prediction Trending Towards Machine Learning

Abstract

In The Business World, The Stock Market Analysis And Prediction Tends To Be More Risk And
Challenges Who Invest Money In The Market. Generally, Several Analysis Are Carried Towards To The
Investigations And Action Taken Towards The Intelligence Of Future Market Movements. Societal Media
Data’s Were Been Used To Elevated Impact Of Stock Market, This Societal Data Were Help To Predicate
Easily. Usually The Prediction Model Will Be Higly Based On The Day By Day Or Monthly Report
Structure. All The Prediction Results That Are Analyzed Helps To Estimate And Project The Next Day
Rate In The Market. By Using The Prediction Techniques Like Multiple Linear Regression And Random
Forest Algorithm In Machine Learning, It Is Easy To Calculate The Stock Market Open Price In The
Upcoming Days. In This Research Work, Involves RFA Prediction Algorithm Which Is Studied To
Construct And Develop A Prediction Model. In Addition, RFA Analysis And Report Is Compared And
Studied With MLR Report. By The Comparison, The Study Proved That The Fine-Tuning And High
Accuracy Of Market Value Is Predicted Effectively With The Help Of RFA.