Stock Market Prediction using Data Mining Techniques

被引:0
|
作者
Maini, Sahaj Singh [1 ]
Govinda, K. [1 ]
机构
[1] VIT, SCOPE, Vellore, Tamil Nadu, India
关键词
Machine Learning; Random Forest Model; Stock Market; Support Vector Machine; SUPPORT VECTOR MACHINES;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:654 / 661
页数:8
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