Data Mining: Cluster analysis doing manually chapter 10

K-means clustering Algorithm for manually finding from observation:

Step 1: Take mean value

Step 2: Find nearest number of mean and put in cluster

Step 3: Repeat one and two until we get same mean

K={2,3,4,10,11,12,20,25,30}

k=2 [it means we have to create 2 clusters]

iter1:

m1=4   m2=12

k1={2,3,4}   [according to nearest distance of 4]

so mean m1=3

k2={10,11,12,20,25,30}

m2=108/6=18

iter2:

k1={2,3,4,10}

m1=4.75==approc(5)

k2={11,12,20,25,30}

m2=19.6==approx(20)

Iter 3:
K1={2,3,4,10,11,12} K2={20,25,30}
m1=7 m2=25

k1={2,3,4,10,11,12} k2={20,25,30}

m1=7, m2=25

Same mean twice. Thus we are getting same mean we have to stop.

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