Quick Answer
The answer is a parallel coordinates plot. This visualization technique is the most appropriate for imbalanced classes because it can simultaneously display multiple numerical features along parallel axes, with lines colored by the target class, making it easy to spot distinct patterns or clusters for the minority class (1% positive) versus the majority class in high-dimensional space. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of exploratory data analysis for imbalanced datasets, a common scenario where standard plots like scatter plot matrices become cluttered with many features, while histograms and box plots fail to show feature interactions. A common trap is choosing a univariate plot, but remember that parallel coordinates excel at revealing multivariate relationships across classes. Memory tip: think of parallel coordinates as “class-colored spaghetti” that helps you trace the minority class’s path through all features at once.
This MLS-C01 practice question tests your understanding of exploratory data analysis. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 data scientist is working with a dataset that has imbalanced classes (1% positive). They want to explore the data before modeling. Which visualization technique is most appropriate to understand the distribution of features with respect to the target class?
Box plots grouped by class
Why wrong: Incorrect: Box plots are also univariate.
Parallel coordinates plot
Correct: Parallel coordinates can display multiple features and highlight class separations.
Histograms overlaid by class
Why wrong: Incorrect: Histograms only show one feature at a time.
Scatter plot matrix
Why wrong: Incorrect: With many features, scatter plot matrices become unreadable.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Parallel coordinates plot
Option B is correct because parallel coordinates plot can show feature patterns for minority vs majority class in high dimensions. Option A is wrong because scatter plot matrices become cluttered with many features. Option C is wrong because histograms are univariate and do not show interaction. Option D is wrong because box plots are univariate.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Box plots grouped by class
Why it's wrong here
Incorrect: Box plots are also univariate.
Parallel coordinates plot
Why this is correct
Correct: Parallel coordinates can display multiple features and highlight class separations.
Related concept
Static NAT maps one inside address to one outside address.
Histograms overlaid by class
Why it's wrong here
Incorrect: Histograms only show one feature at a time.
Scatter plot matrix
Why it's wrong here
Incorrect: With many features, scatter plot matrices become unreadable.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Trap categories for this question
Command / output trap
Incorrect: Histograms only show one feature at a time.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. 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
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
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FAQ
Exploratory Data Analysis — This question tests Exploratory Data Analysis — Static NAT maps one inside address to one outside address..
The correct answer is: Parallel coordinates plot — Option B is correct because parallel coordinates plot can show feature patterns for minority vs majority class in high dimensions. Option A is wrong because scatter plot matrices become cluttered with many features. Option C is wrong because histograms are univariate and do not show interaction. Option D is wrong because box plots are univariate.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related MLS-C01 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
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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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