Question

Which of the following algorithm is most sensitive to outliers?
A. K-means clustering algorithm
B. K-medians clustering algorithm
C. K-modes clustering algorithm
D. K-medoids clustering algorithm​

Answer 1

Answer:

A. K-means clustering algorithm

Step-by-step explanation:

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Answer 2

K-means clustering algorithm

Step-by-step explanation:

k-means clustering algorithm computes the centroid and iterates until we it finds optimal centroid. Here the data points are assigned to a cluster in such a manner that the sum of the squared distance between the data points and centroid would be minimum.

K-means clustering algorithm is sensitive to outliers because a means is easily influenced by extreme values.