Predictive analysis of stock prices through scikit-learn: Machine learning in python
- Title
- Predictive analysis of stock prices through scikit-learn: Machine learning in python
- Creator
- Mishra V.K.; Binyala R.; Sharma P.; Singh S.
- Description
- Scikit-learn, a tool for developing machine learning algorithms, is a standard library of python. Through Scikit-learn, a trained model for predictive analysis can be developed. Such models aim to provide accurate predictions. Stock predictions are based on changes and patterns identified in the historical dataset. Following the trends and patterns of the historical changes of stocks, machine learning algorithms can be developed for achieving accurate outcomes. An effective model is developed, which enhance the working pattern or performance of the machine that further helps to draw a precise analysis of stocks. 2023 Scrivener Publishing LLC.
- Source
- Mathematics and Computer Science, Vol-1, pp. 397-404.
- Date
- 2023-01-01
- Publisher
- Wiley Blackwell
- Subject
- Machine learning; Predictive analysis; Scikit-learn; Stock market
- Coverage
- Mishra V.K., SCSE, Galgotias University, Uttar Pradesh, India; Binyala R., School of Business and Management, Christ (Deemed to be University), Delhi NCR, India; Sharma P., School of Business and Management, Christ (Deemed to be University), Delhi NCR, India; Singh S., School of Business and Management, Christ (Deemed to be University), Delhi NCR, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-111987983-1; 978-111987967-1
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Mishra V.K.; Binyala R.; Sharma P.; Singh S., “Predictive analysis of stock prices through scikit-learn: Machine learning in python,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/18255.