K Means Algorithm

Partitioning Method-

In partitioning method the the ‘n’ is the object group and that group are combined with group notation ‘K’, where each partition represent one cluster. In partitioning method the cluster is a group of undefined or objects with similar characteristics.

There are two classified partitioning method are as follows-

1. K means 
2. k mediads

K means-

k-means is one of the simplest unsupervised learning algorithm. Which follows a easy way and simplest formation for defining clustering from undefined objects. K means algorithm used for divide ‘X’ in different cluster and shows which is suitable for X” and accurate cluster to and denote accurate cluster for predict a value.

Advantages of K means algorithm-

1. It is fast and easy to understand.
2. Gives a better result when objects are different from each others.

Disadvantages for understanding k-means algorithm-

1.  It is unable to handle noisy data.
2. That algorithm are fails for Non linear data set.