You are considering the K-Means clustering algorithm with Euclidean distance. Given points (10,10), (12,12), (11,13), (1

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You are considering the K-Means clustering algorithm with
Euclidean distance. Given points (10,10), (12,12), (11,13),
(12,11), (-1, -2) and
(-12, -1). Your task is to calculate the coordinate of the centroid
of these points. You need to show your calculation steps.
Considering the K-Means clustering algorithm with Euclidean
distance measuring similarity between points. Given the centroids
with coordinates A=(10, 10) and B=(1, 1), your task is to put
all points with coordinates p1=(11,11), p2=(4,4), p3=(15,15),
p4=(-8,-8) and p5=(100, 100) to its closest cluster (either A or B)
based on Euclidean distance. With grouped points, show how to
update coordinates of centroids. You need to show your
calculation steps.
Compared with the K-Means clustering algorithm, please explain
the advantages and disadvantages of the Agglomerative algorithm for
solving a clustering task.