Volume 23 , Issue 3 , PP: 245-261, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Firuz Kamalov 1 * , Said Elnaffar 2 , Ikhlaas Gurrib 3 , Aswani Cherukuri 4
Doi: https://doi.org/10.54216/IJNS.230321
Regression analysis is a widely used tool in several fields. In this paper, we propose a comprehensive, multistep regression model for financial forecasting. The proposed hybrid model combines preprocessing, feature selection, and cross-validation to obtain a powerful approach to forecasting. The extension of the proposed model to neutrosophic sets is discussed. The model is applied to the case study of real estate prices. The results demonstrate the efficacy of the model.
regression analysis , feature selection , preprocessing , financial forecasting , hybrid model , neutrosophic set
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