Answer: Logistic regression model

## Explanation Logistic regression is a linear model that assigns weights to input features, making it highly interpretable. These weights can be viewed and adjusted by domain experts based on their knowledge — which directly satisfies the requirement of allowing employees to 'view and adjust the weights assigned to different variables.' ### Why Logistic Regression is the Best Choice: 1. **Interpretability**: Logistic regression provides clear, understandable coefficients (weights) for each input variable 2. **Adjustability**: Domain experts can easily modify these weights based on their business knowledge 3. **Transparency**: The model's decision-making process is transparent and explainable ### Why Other Options Are Not Suitable: - **Deep learning models (B and D)**: These are often 'black boxes' — difficult to interpret and adjust weights meaningfully without extensive technical expertise - **K-NN (C)**: This is instance-based and doesn't use adjustable weights in the same way; it relies on distance metrics and nearest neighbors Thus, **Logistic regression** is the most suitable model for this use case due to its transparency and tunability, allowing business users to incorporate their domain expertise directly into the model.

Author: Ritesh Yadav