Answer-first summary for fast verification
Answer: There are very few occurrences of mutations relative to normal samples., You expect future mutations to have different features from the mutated samples in the database.
Unsupervised anomaly detection is ideal for scenarios with rare anomalies and when future anomalies are expected to have different features from those seen before. Option A is correct because unsupervised anomaly detection assumes anomalies occur very rarely in the data. Option C is correct because this method is effective when future anomalies are expected to differ from the previously seen anomalies. Thus, the method doesn't rely on prior known patterns.
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You are tasked with classifying future tissue samples from a database containing information about existing tissue samples, categorizing them as either normal or mutated. You have decided to evaluate an unsupervised anomaly detection method for this classification task. Which two characteristics support the use of this method? (Choose two.)
A
There are very few occurrences of mutations relative to normal samples.
B
There are roughly equal occurrences of both normal and mutated samples in the database.
C
You expect future mutations to have different features from the mutated samples in the database.
D
You expect future mutations to have similar features to the mutated samples in the database.
E
You already have labels for which samples are mutated and which are normal in the database.
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