Câu 9: RAI: Risk and Artificial Intelligence

A credit risk analyst is preparing data for a K-nearest neighbors (KNN) model used to flag potentially risky loan applications. Two features are selected:Annual Income (dollars, X-axis)Debt-to-Income (DTI) Ratio (percentage, Y=axis)Before modeling, the analyst visualizes the raw data shown below. Annual income ranges from $30,000 to $150,000, while DTI ratios range from 10% to 50%. The analyst intends to use Euclidean distance to identify similar borrowers. Given the pattern shown in the plot, which data preparation step would be most appropriate before fitting the model?

1. A. Use the raw variables because KNN is robust to differences in feature scale.
2. B. Scale both variables so that income and DTI contribute comparably to distance calculations. — đáp án hiện tại
3. C. Apply a logarithmic transformation only to Debt-to-Income (DTI) Ratio.
4. D. Apply categorical encoding to both variables to eliminate scale differences.