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...
I tiakina i:
| Ngā kaituhi matua: | , |
|---|---|
| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
Elsevier
2024-12-01
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| Rangatū: | Borsa Istanbul Review |
| Ngā marau: | |
| Urunga tuihono: | http://www.sciencedirect.com/science/article/pii/S2214845024001558 |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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