Long-Term vs. Short-Term Forecasting Data Scientist's Strategies for Different Horizons

Sowmya Ramesh Kumar

Abstract: Forecasting is a critical aspect of data science, and the choice between long - term and short - term forecasting strategies depends on the nature of the data, the objectives of the analysis, and the specific needs of the application. In this discussion, we will explore the distinctions between long - term and short - term forecasting, the strategies employed by expert data scientists for each horizon, and the considerations that influence their decision - making.

Keywords: Long Term Forecasting, Short term forecasting, seasonality, decomposition, forecasting, modeling

How to Cite?: Sowmya Ramesh Kumar, "Long-Term vs. Short-Term Forecasting Data Scientist's Strategies for Different Horizons", Volume 10 Issue 6, June 2021, International Journal of Science and Research (IJSR), Pages: 1796-1797, https://www.ijsr.net/getabstract.php?paperid=SR24213014558, DOI: https://dx.doi.org/10.21275/SR24213014558