A cybersecurity team wants to detect unusual network traffic patterns that may indicate a new type of attack. They have a large dataset of normal network traffic but no examples of attacks. Which approach should they use?

Use anomaly detection to identify traffic that deviates from normal patterns.

Use PCA to reduce the dimensionality of the traffic data.

Apply association rule mining to find frequent traffic patterns.

Train a supervised classifier on labeled normal and attack traffic.

A retail chain wants to use association rule mining to find items frequently bought together. They have a very large transaction database. Which consideration is most important when choosing the minimum support threshold?

A higher minimum support will always produce more useful rules.

The minimum support should be set to 100% to ensure all rules are valid.

The minimum support should be set to 0% to find all possible rules.

A lower minimum support will generate more rules, including potentially spurious ones.

What is the main purpose of dimensionality reduction in machine learning?

To group similar data points into clusters.

To add labels to unlabeled data.

To increase the number of features to improve model accuracy.

To reduce the number of features while preserving important information.

What is the primary learning goal of an unsupervised learning algorithm?

To assign each input to a predefined category.

To minimize the error between predicted and actual labels.

To identify the underlying structure or relationships in the data.

To predict a numeric value for each input example.

In which scenario would unsupervised learning be most appropriate?

When the dataset has no labels and you want to explore its natural structure.

When you need to predict a continuous value from historical data.

When you have a small dataset and need to improve accuracy by adding more features.

When you have labeled data and want to predict a category for new inputs.

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Domain 3Objective 2

Unsupervised Learning CT-AI Practice Questions (Page 4)

Part of the Domain 3: Machine Learning (ML) - Overview domain, which makes up ~15% of our current practice bank. ISTQB does not publish an official question count, but from its 60-minute exam (~25–40 total, ~4–6 in this domain), expect 1–1 from this objective — we provide 30 practice questions to prepare you well beyond it. (estimate)

30questions here

6free pages

6concepts

Questions 16–20

16application · medium
A cybersecurity team wants to detect unusual network traffic patterns that may indicate a new type of attack. They have a large dataset of normal network traffic but no examples of attacks. Which approach should they use?
Select an answer first
17expert · hard
A retail chain wants to use association rule mining to find items frequently bought together. They have a very large transaction database. Which consideration is most important when choosing the minimum support threshold?
Select an answer first
18foundation · easy
What is the main purpose of dimensionality reduction in machine learning?
Select an answer first
19foundation · easy
What is the primary learning goal of an unsupervised learning algorithm?
Select an answer first
20foundation · easy
In which scenario would unsupervised learning be most appropriate?
Select an answer first

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