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PROFESSIONAL-DATA-ENGINEER · Question #14
You want to use a database of information about tissue samples to classify future tissue samples as either normal or mutated. You are evaluating an unsupervised anomaly detection method for classifyin
The correct answer is A. There are very few occurrences of mutations relative to normal samples. D. You expect future mutations to have similar features to the mutated samples in the database.. are normal by looking for instances that seem to fit least to the remainder of the data set. https://en.wikipedia.org/wiki/Anomaly_detection
Submitted by lars.no· Mar 30, 2026Operationalizing machine learning models
Question
You want to use a database of information about tissue samples to classify future tissue samples as either normal or mutated. You are evaluating an unsupervised anomaly detection method for classifying the tissue samples. Which two characteristic support this method? (Choose two.)
Options
- AThere are very few occurrences of mutations relative to normal samples.
- BThere are roughly equal occurrences of both normal and mutated samples in the database.
- CYou expect future mutations to have different features from the mutated samples in the database.
- DYou expect future mutations to have similar features to the mutated samples in the database.
- EYou already have labels for which samples are mutated and which are normal in the database.
How the community answered
(31 responses)- A61% (19)
- B23% (7)
- C6% (2)
- E10% (3)
Explanation
are normal by looking for instances that seem to fit least to the remainder of the data set. https://en.wikipedia.org/wiki/Anomaly_detection
Topics
#anomaly detection#unsupervised learning#class imbalance#classification strategy
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