Choosing number of clusters in k means

Question

I want to cluster a large sample of data and for it I am using k means function in MATLAB. The problem is that it returns a matrix with all the data sorted in the number of clusters I specify.

How can I know which number of clusters is optimal.

I thought that if I would get the equal number of elements in each cluster that would be optimal but this never happens. Rather it can go on clustering the data for any number I put.

Please help...

Answer 1

I read and I think an answer to this could be :- In kmeans we are trying to partition the data according to the means as the data comes so theoretically our best dataset would be where each partition has equal number of data.

I used kmeans++ which was a better algorithm than kmeans because it does not initialise a random value and then iterated over the number of partitions till the sizes of partitions were almost equal. This was an approximate figure as say for 3 i got 2180,729,1219 and for 4 i was getting 30,2422, 1556,120 so I chose 3 as my final answer............