Implemetation of machine learning: machine learning for decision-making strategies of insurance companies
Iavorskii, Bogdan (A.A. 2024/2025) Implemetation of machine learning: machine learning for decision-making strategies of insurance companies. Tesi di Laurea in Artificial intelligence and machine learning, Luiss Guido Carli, relatore Giuseppe Francesco Italiano, pp. 39. [Bachelor's Degree Thesis]
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Abstract/Index
Background, motivation and state of the art. Problem statement. Theoretical foundations of machine learning. Supervised learning overview. Relevant machine learning algorithms. Model evaluation metrics. Data collection and preprocessing made for research. Description of given data. Data cleaning and missing value imputation. Data preprocessing. Exploratory data analysis. Machine learning models implementation for research. Feature engineering and variance inflation factor. Hyperparameter tuning. Evaluation of a classification model. Preparing regression dataset and removing outliers for the regression model. Evaluation of regression model and predicting the claim amount. Calculating the sum of payments for the next year and interpretation of results. Analysis of working process and potential implications. Feature importance analysis. Limitations of the model. Practical implications for insurance companies. Comparison with traditional decision-making approaches. Challenges of implementation of machine learning for insurance companies. Practical challenges. Ethical and regulatory considerations in insurance. Nature and types of insurance data.
References
Bibliografia: p. 38.
| 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: | Artificial intelligence and machine learning |
| Thesis Supervisor: | Italiano, Giuseppe Francesco |
| Academic Year: | 2024/2025 |
| Session: | Summer |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 03 Dec 2025 14:17 |
| Last Modified: | 03 Dec 2025 14:17 |
| URI: | https://tesi.luiss.it/id/eprint/44184 |
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