Learning Path
Question & Answer
Choose the Best Answer
By finding the closest embedded vector to the input based on signed distance
By averaging the embedded vectors of all classes
By selecting the class with the most members in the training set
By calculating the Euclidean distance to all training inputs
Understanding the Answer
Let's break down why this is correct
The method looks for the embedded vector that is closest to the new input. Other options are incorrect because Some think averaging all class vectors gives the best match; A misconception is that the biggest class always wins.
Key Concepts
Nearest-Neighbor Un-embedding
easy level question
understand
Deep Dive: Nearest-Neighbor Un-embedding
Master the fundamentals
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.
Ready to Master More Topics?
Join thousands of students using Seekh's interactive learning platform to excel in their studies with personalized practice and detailed explanations.