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.

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Definitions:

Pancreatic Islets

Groups of pancreatic cells that produce hormones, including insulin and glucagon, which regulate blood sugar levels.

Secretory Cells

Cells that produce and release substances such as enzymes, hormones, or mucus.

Pancreatic Acini

The small clusters of cells in the pancreas that produce digestive enzymes.

Digestive Enzymes

Proteins secreted by the digestive system that break down food into nutrients that can be absorbed into the bloodstream.