TY  - JOUR
TI  - Analysis of K-Mean Algorithm
AU  - Vinaya Durga M
AU  -  Ganapathi Sharma K
JO  - International Journal of Scientific Research in Computer Science, Engineering and Information Technology
PB  - Technoscience Academy
DA  - 2020/02/25
PY  - 2020
DO  - https://doi.org/10.32628/IJSRCSEIT
UR  - https://ijsrcseit.com/CSEIT206126
VL  - 6
IS  - 1
SP  - 133	
EP  - 136
AB  - Clustering is one among the foremost common preliminary knowledge associates to analysis technique to get an intuition regarding the structure of the info. It is often outlined because the task of characteristic subgroups within the knowledge such knowledge points within the same subgroup (cluster) area unit are similar whereas knowledge points totally different in numerous clusters area different. There are several algorithms which deals with unsupervised learning. K means algorithm is one of such algorithm. Kmeans algorithm is an iterative algorithm that tries to partition the dataset into K pre-defined distinct non-overlapping subgroups (clusters) where each data point belongs to only one group. It tries to make the inter-cluster data points as similar as possible while also keeping the clusters as far as possible. It assigns data points to a cluster such that the sum of the squared distance between the data points and the cluster&rsquo;s centroid , that is (x2-x1)<sup>2</sup>+ (y2-y1)<sup>2</sup>