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Stock market prediction using data mining techniques
Maini S.S,
Published in IEEE
Pages: 654 - 661
Stock market prediction has been an area of interest for investors as well as researchers for many years due to its volatile, complex and regularly changing in nature, making it difficult to make reliable predictions This paper proposes an approach towards prediction of stock market trends using machine learning models like Random Forest model and Support Vector Machine. The Random Forest model is an ensemble learning method that has been an exceedingly successful model for classification and regression. Support vector machine is a machine learning model for classification. However, this model is mostly used for classification. These techniques are used to forecast whether the price of a stock in the future will be higher than its price on a given day, based on historical data while providing an in-depth understanding of the models being used. © 2017 IEEE.
About the journal
JournalData powered by Typeset2017 International Conference on Intelligent Sustainable Systems (ICISS)
PublisherData powered by TypesetIEEE
Open Access0