Quick Answer
The correct answer is to compare feature correlations with target in training and test sets, use a time-based split, and examine distribution differences between train and test sets. These three EDA checks are essential for detecting data leakage in time series features because leakage often occurs when future information inadvertently influences the training data. Comparing correlations helps reveal if a feature has an unrealistically strong relationship with the target in training but not in test, while a chronological split exposes whether future data has leaked backward into the training window. Distribution differences, such as a shift in a time-based feature’s values between sets, can also signal that the training set contains data from a later time period. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your ability to identify practical EDA techniques for leakage detection, a common trap being to confuse dimensionality reduction or clustering with leakage checks. Remember the mnemonic “C-T-D” for Correlation, Time split, and Distribution—three checks that catch time-based leakage.
This MLS-C01 practice question tests your understanding of exploratory data analysis. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A machine learning team is analyzing a dataset with 10,000 rows and 200 features. They suspect data leakage due to time-based features. Which THREE EDA checks should they perform?
Plot distribution of each feature in training vs. test sets
Why D is correct
Apply PCA and check if first two components separate train/test
Why wrong: Why E is wrong
Check whether the dataset is sorted by time and if any feature uses future information
Why C is correct
Compare feature correlations with target in training and test sets
Why A is correct
Perform k-means clustering on the whole dataset
Why wrong: Why B is wrong
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Plot distribution of each feature in training vs. test sets
Option A is correct because feature correlation with target in training vs. test sets may indicate leakage. Option C is correct because time-based split (chronological) can reveal if future data leaks into training. Option D is correct because distribution differences between train and test sets can indicate leakage (e.g., train has future data). Option B is wrong because clustering is not directly helpful for leakage detection. Option E is wrong because PCA is for dimensionality reduction, not leakage detection.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Plot distribution of each feature in training vs. test sets
Why this is correct
Why D is correct
Related concept
Read the scenario before looking for a memorised answer.
Apply PCA and check if first two components separate train/test
Why it's wrong here
Why E is wrong
Check whether the dataset is sorted by time and if any feature uses future information
Why this is correct
Why C is correct
Related concept
Read the scenario before looking for a memorised answer.
Compare feature correlations with target in training and test sets
Why this is correct
Why A is correct
Related concept
Read the scenario before looking for a memorised answer.
Perform k-means clustering on the whole dataset
Why it's wrong here
Why B is wrong
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Read the scenario before looking for a memorised answer..
The correct answer is: Plot distribution of each feature in training vs. test sets — Option A is correct because feature correlation with target in training vs. test sets may indicate leakage. Option C is correct because time-based split (chronological) can reveal if future data leaks into training. Option D is correct because distribution differences between train and test sets can indicate leakage (e.g., train has future data). Option B is wrong because clustering is not directly helpful for leakage detection. Option E is wrong because PCA is for dimensionality reduction, not leakage detection.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
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.
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