Machine learning algorithms: focus on tree based and gradient boosting algorithms to predict NYSE investments
Cardile, Demetrio Francesco (A.A. 2023/2024) Machine learning algorithms: focus on tree based and gradient boosting algorithms to predict NYSE investments. Tesi di Laurea in Algorithmis, Luiss Guido Carli, relatore Irene Finocchi, pp. 62. [Bachelor's Degree Thesis]
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Abstract/Index
Introduction to artificial intelligence and machine learning. Deep learning. Financial applications of artificial intelligence and machine learning. Machine learning for stock market prediction. Machine learning for fraud detection. Machine learning for credit scoring. Predictive modeling on NYSE investments. Overview of the dataset. Metrics of interest. Data preprocessing. Inspecting for duplicates. Inspecting for missing values. Removing outliers. Removing variables. Handling imbalanced data. Transforming given variables into factor type. Scaling and standardization of variables. Exploratory data analysis (EDA). Investigating distribution of numerical variables. Model implementation.
References
Bibliografia: p. 61.
| Thesis Type: | Bachelor's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Bachelor's Degree Programs > Bachelor's Degree Program in Management and Computer Science, English language (L-18) |
| Chair: | Algorithmis |
| Thesis Supervisor: | Finocchi, Irene |
| Academic Year: | 2023/2024 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 17 Oct 2024 12:36 |
| Last Modified: | 17 Oct 2024 12:36 |
| URI: | https://tesi.luiss.it/id/eprint/40091 |
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