Which two characteristic support this method?

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.)
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.

View Answer

Answer: AD

Explanation:

Unsupervised anomaly detection techniques detect anomalies in an unlabeled test data set under the assumption that the majority of the instances in the data set 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