A Comparative Analysis of Traditional and Machine Learning Forecasting Techniques
- Title
- A Comparative Analysis of Traditional and Machine Learning Forecasting Techniques
- Creator
- Jacob L.; Thomas K.T.
- Description
- Forecasting is the process of making predictions or estimates about future events or conditions based on historical data, trends, and patterns. It involves analyzing past data and using statistical or other quantitative methods to project future outcomes, such as sales figures, market trends, weather patterns, or financial performance. Forecasting can be used in a wide range of fields, including economics, finance, business, weather forecasting, and sports. The accuracy of a forecast depends on the quality of the data, the methods used, and the assumptions made about the future. 2024 Sachi Nandan Mohanty, Preethi Nanjundan and Tejaswini Kar.
- Source
- Artificial Intelligence in Forecasting: Tools and Techniques, pp. 190-218.
- Date
- 2024-01-01
- Publisher
- CRC Press
- Coverage
- Jacob L., Department of Data Science, Christ University, India; Thomas K.T., Department of Data Science, Christ University, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-104005150-4; 978-103250615-9
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Jacob L.; Thomas K.T., “A Comparative Analysis of Traditional and Machine Learning Forecasting Techniques,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/18068.