AWS Certified Machine Learning – Specialty — Question 239

A data scientist wants to improve the fit of a machine learning (ML) model that predicts house prices. The data scientist makes a first attempt to fit the model, but the fitted model has poor accuracy on both the training dataset and the test dataset.

Which steps must the data scientist take to improve model accuracy? (Choose three.)

Answer options

• A. Increase the amount of regularization that the model uses.
• B. Decrease the amount of regularization that the model uses.
• C. Increase the number of training examples that that model uses.
• D. Increase the number of test examples that the model uses.
• E. Increase the number of model features that the model uses.
• F. Decrease the number of model features that the model uses.

Correct answer: B, C, E

Explanation

The correct steps to enhance model accuracy involve decreasing regularization (B), which allows the model to learn more from the training data, increasing the number of training examples (C) to provide the model with more information, and increasing the number of features (E) to help the model capture more complex patterns. Increasing regularization (A) would further restrict the model's learning, while increasing test examples (D) does not directly improve training accuracy, and decreasing features (F) could lead to loss of important information.