You need to explain why you think normalisation is a good idea. Transforming your data in some way is not to be undertaken without serious reason.

What kind of data have you got, and why they normalisation?

Souadfel Salima,

Theoretically, normalisation is used to transform data to make them comparable and often unitless. The best way to normalise is to divide each element in a data set by the largest value thereby making the largest element to be 1.

If you are more specific, I should be able to suggest better.

Thank you.

Thank you for your reply

I am working on data clustering when the number of the clusters is unknown.

I am using normalization to give the same importance to all the variables of the data set.

From my test, i observed that the clustering results vary according to the normalization method for some data set like iris, wine glass.

So my question is does  normalization of data improve the clustering results?

Thank you.

I believe that the answer relies on how clustering is performed.

Depending on the algorithm you use, for example DBSCAN, which is based on fixed thresholding, such values may make sense when data is normalized and not when the data is not.