easyMultiple ChoiceObjective-mapped
MLA-C01 Practice Question: A data scientist is using Amazon SageMaker to…
A data scientist is using Amazon SageMaker to train a linear regression model. After training, the scientist notices that the training and validation errors are both low, but the model performs poorly on new test data. What is the MOST likely cause?
⚠ Common exam trap
Many exam-takers confuse overfitting (low training error, high validation error) with data leakage (low training and validation errors, but poor test performance), so they incorrectly select Option C without recognizing that the validation error is also low.
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
✓
There is data leakage from the validation set into the training set
Data leakage from the validation set into the training set would allow the model to learn patterns that are not present in truly unseen data, leading to artificially low training and validation errors but poor generalization to new test data. In SageMaker, this can occur if the dataset is not properly split before feature engineering or if preprocessing (e.g., scaling or imputation) is applied to the entire dataset before splitting, causing the validation set to influence the training process.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
There is data leakage from the validation set into the training set
Why this is correct
Data leakage artificially inflates performance on validation but fails on true unseen data.
- ✗
The features are not scaled properly
Why it's wrong here
Improper scaling affects convergence speed but not generalization performance if model converged.
- ✗
The model is overfitting the training data
Why it's wrong here
Overfitting would cause low training error but high validation error, not low validation error.
- ✗
The model has high bias
Why it's wrong here
High bias would result in high training error as well.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLA-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 MLA-C01 exam.