Learning Path
Question & Answer
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The method of vector embedding used
The signed distances to decision boundaries
The number of classes embedded
The dimensionality of the input space
Understanding the Answer
Let's break down why this is correct
Signed distances to decision boundaries show how close a point is to each class line. Other options are incorrect because The embedding method only creates the space; it does not decide which neighbor is chosen; The number of classes does not change how distances are measured.
Key Concepts
Nearest-Neighbor Un-embedding
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Deep Dive: Nearest-Neighbor Un-embedding
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Definition
Nearest-neighbor un-embedding involves embedding classes as vectors and determining the closest vector to a given prediction. It focuses on calculating signed distances to decision boundaries for effective classification.
Topic Definition
Nearest-neighbor un-embedding involves embedding classes as vectors and determining the closest vector to a given prediction. It focuses on calculating signed distances to decision boundaries for effective classification.
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