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Question 20 - H13-311_V3.5 discussion

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Which of the following statements are true about the k-nearest neighbors (k-NN) algorithm?

A.
k-NN typically uses the mean value method to predict regression.
Answers
A.
k-NN typically uses the mean value method to predict regression.
B.
k-NN typically uses the majority voting method to predict classification.
Answers
B.
k-NN typically uses the majority voting method to predict classification.
C.
k-NN is a parametric method often used for datasets with regular decision boundaries.
Answers
C.
k-NN is a parametric method often used for datasets with regular decision boundaries.
D.
The k-NN algorithm determines which class an object belongs to based on the class to which most of the object's k nearest neighbors belong.
Answers
D.
The k-NN algorithm determines which class an object belongs to based on the class to which most of the object's k nearest neighbors belong.
Suggested answer: B, D

Explanation:

The k-nearest neighbors (k-NN) algorithm is a non-parametric algorithm used for both classification and regression. In classification tasks, it typically uses majority voting to assign a label to a new instance based on the most common class among its nearest neighbors. The algorithm works by calculating the distance (often using Euclidean distance) between the query point and the points in the dataset, and then assigning the query point to the class that is most frequent among its k nearest neighbors.

For regression tasks, k-NN can predict the outcome based on the mean of the values of the k nearest neighbors, although this is less common than its classification use.

asked 26/09/2024
sd sdg
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