K-Mean Clustering

Clustering comes under unsupervised learning algorithm : 

for clustering algorithm uses are  : k- mean clustering  

clustering is the process of partitioning group of data points

into small number of clusters

k means is a clustering method that aims to find the position of the cluster

that minimize the distance from data points to the cluster

k-means clustering is one of the simplest algorithms which uses unsupervised learning method to solve known clustering issues. k-means clustering require following two inputs.

1. k = number of clusters
2. Training set(m) = {x1, x2, x3,……….., xm}

Let’s say you have an unlabeled data set like the one shown below and you want to group this data into clusters.

take mean value
find nearest number and mean and put into cluster
repeat one and two until we not get same mean
example :
{2,3,4,10,11,12,20,25,30}
data set
creating two cluster
m1=4 m2=12

k1={2,3,4,} m1=3
k2={10,11,12,20,25,30} m2=18
========================

k1{2,3,4,10,11,12} m1=5
k2{20,25,30} m2=20
=========================
k1{2,3,4,10,11,12} m1=7
k2{20,25,30} m2=25