MLS-C01 Modeling Practice Question
A company is using Amazon SageMaker to train a linear learner model for predicting customer lifetime value. The target variable is right-skewed with a long tail. The data scientist applies a log transformation to the target variable and trains the model. The model achieves a low root mean squared error (RMSE) on the log scale. However, when the predictions are exponentiated back to the original scale, the RMSE is much higher. Which step should the data scientist take to improve the model's performance on the original scale?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use a loss function that models the original distribution, such as Poisson or Tweedie
Using a loss function like Poisson or Tweedie directly models the non-negative, skewed distribution of the target variable in its original scale, which avoids the bias introduced by log transformation when predicting on the original scale. Option A (increase regularization) may not address the scale mismatch. Option B (remove outliers) could discard valuable data. Option D (use a deep learning model) might not solve the fundamental issue of loss function selection.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the regularization strength
Why it's wrong here
Regularization does not address the transformation issue.
- ✗
Remove outliers from the training data
Why it's wrong here
Removing outliers may discard valuable data.
- ✓
Use a loss function that models the original distribution, such as Poisson or Tweedie
Why this is correct
These loss functions handle skewed distributions better.
- ✗
Use a deep learning model instead of linear learner
Why it's wrong here
Deep learning may not inherently solve the distribution mismatch.
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Written by Johnson Ajibi, MSc IT Security
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This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.