The good, the better and the challenging: Insights into predicting high-growth firms using machine learning
This study aims to classify high-growth firms using several machine learning algorithms, including K-Nearest Neighbors, Logistic Regression with L1 (Lasso) and L2 (Ridge) Regularization, XGBoost, Gradient Descent, Naive Bayes and Random Forest. Leveraging a dataset composed of financial metrics and...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Borsa Istanbul Review |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214845024001558 |
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