A Data Mining approach on the Performance of Machine Learning Methods for Share Price Forecasting using the Weka Environment
- Title
- A Data Mining approach on the Performance of Machine Learning Methods for Share Price Forecasting using the Weka Environment
- Creator
- Uma Devi A.; Vishal Kumar R.; Shanmugha Priya P.; Amzad Basha M.S.; Martha Sucharitha M.; Oveis P.M.
- Description
- It is widely agreed that the share price is too volatile to be reliably predicted. Several experts have worked to improve the likelihood of generating a profit from share investing using various approaches and methods. When used in reality, these methods and algorithms often have too low of a success rate to be helpful. The extreme volatility of the marketplace is a significant contributor. This article demonstrates the use of data mining methods like WEKA to study share prices. For this research's sake, we have selected a HCL Tech share. Multilayer perceptron's, Gaussian Process and Sequential minimal optimization have been employed as the three prediction methods. These algorithms that develop optimal rules for share market analysis have been incorporated into Weka. We have transformed the attributes of open, high, low, close and adj-close prices forecasted share for the next 30 days. Compare actual and predicted values of three models' side by side. We have visualized 1step ahead and the future forecast of three models. The Evaluation metrics of RMSE, MAPE, MSE, and MAE are calculated. The outcomes achieved by the three methods have been contrasted. Our experimental findings show that Sequential minimal optimization provided more precise results than the other method on this dataset. 2023 IEEE.
- Source
- 2023 5th International Conference on Electrical, Computer and Communication Technologies, ICECCT 2023
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Data Mining; Gaussian Process and Weka; Multi-layer Perceptron; SMO Reg; Stock Price Prediction
- Coverage
- Uma Devi A., SRM Valliammai Engineering College, Department of Management Studies, Chengalpattu, India; Vishal Kumar R., Kalasaligam Academy of Research and Education, Department of Business Administration, Coimbatore, India; Shanmugha Priya P., Sri Krishna College of Technology, Coimbatore, India; Amzad Basha M.S., GITAM School of Business, Gandhi Institute of Technology and Management (Deemed to Be University), Bengaluru, India; Martha Sucharitha M., Christ (Deemed to Be University), Department of Professional Studies, Bengaluru, India; Oveis P.M., GITAM School of Business, Gandhi Institute of Technology and Management (Deemed to Be University), Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-166549360-4
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Uma Devi A.; Vishal Kumar R.; Shanmugha Priya P.; Amzad Basha M.S.; Martha Sucharitha M.; Oveis P.M., “A Data Mining approach on the Performance of Machine Learning Methods for Share Price Forecasting using the Weka Environment,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19872.