Research Article
[Retracted] Forecasting Foreign Direct Investment Inflow to Egypt and Determinates: Using Machine Learning Algorithms and ARIMA Model
Table 1
Machine learning algorithms’ performance (data from 1990–2019).
| Models | AUC | CA | F1 | Precision | Recall |
| Gradient Boosting | 0.87 | 0.75 | 0.754 | 0.752 | 0.759 | Logistic regression | 0.87 | 0.690 | 0.669 | 0.665 | 0.690 | Neural network | 0.866 | 0.759 | 0.754 | 0.752 | 0.759 | Random forest | 0.833 | 0.724 | 0.715 | 0.723 | 0.724 | Naïve Bayes | 0.791 | 0.621 | 0.594 | 0.584 | 0.621 | K-nearest neighbors | 0.770 | 0.517 | 0.457 | 0.424 | 0.517 | SVM | 0.741 | 0.655 | 0.621 | 0.614 | 0.655 |
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Source: it is made by the author, depending on the World Bank dataset.
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