A Data Scientist Is Developing a Machine Learning Model to Classify

question 92

Multiple Choice

A Data Scientist is developing a machine learning model to classify whether a financial transaction is fraudulent. The labeled data available for training consists of 100,000 non-fraudulent observations and 1,000 fraudulent observations. The Data Scientist applies the XGBoost algorithm to the data, resulting in the following confusion matrix when the trained model is applied to a previously unseen validation dataset. The accuracy of the model is 99.1%, but the Data Scientist needs to reduce the number of false negatives. Which combination of steps should the Data Scientist take to reduce the number of false negative predictions by the model? (Choose two.)

• A) Change the XGBoost eval_metric parameter to optimize based on Root Mean Square Error (RMS
• E).
• B) Increase the XGBoost scale_pos_weight parameter to adjust the balance of positive and negative weights.
• C) Increase the XGBoost max_depth parameter because the model is currently underfitting the data.
• D) Change the XGBoost eval_metric parameter to optimize based on Area Under the ROC Curve (AU
• C).
• E) Decrease the XGBoost max_depth parameter because the model is currently overfitting the data.

---

Definitions:

Future Performance

Predicted achievements or outcomes of an individual, organization, or system over a specified future period.

Current Performance

The current operational effectiveness and results accomplished by an individual, team, or organization, often evaluated against predetermined benchmarks or objectives.

Succession Management

A strategic process of identifying and developing potential future leaders or senior managers to fill key positions within an organization when they become vacant.

Replacement Planning

The process of identifying and developing new leaders or employees who can replace old leaders when they leave or retire.