Stock Prices Prediction Using Machine Learning
- 23 September 2021
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 79-84
Abstract
More people invest their money in the stock market. However, this kind of investment possesses a lot of risks. Therefore, many works have been done to build a model using Machine Learning algorithm to try to predict the stock price values. In this work, Support Vector Regression (SVR) and Long-Short Term Memory (LSTM) techniques are used to predict the closing price from five different companies. The models are evaluated using one of the common error metrics, which is RMSE (Root Mean Squared Error). The results of the experiment indicate that LSTM has better performance than SVR.Keywords
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