When developing a fraud detection system, what type of machine learning model might you choose and why?
- Decision Trees
- Logistic Regression
- Neural Networks
- Support Vector Machines
In fraud detection, neural networks are often chosen due to their ability to identify complex patterns and relationships in data. They can handle non-linear relationships that may exist in fraudulent activities, making them suitable for this scenario. Logistic regression and decision trees may not capture intricate patterns as effectively, and support vector machines may have limitations in complex data scenarios.
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