ELKI: perform min-max normalization before running k-means

Question

I am using one of the k-means implementations provided by ELKI in my Java project.

I would like to run a min-max normalization before actually running the k-means but I cannot understand what is the right way of doing it using the library API. Can someone point me in the right direction?

Answer 1

new InputStreamDatabaseConnection(is, filterlist, parser))

where filterlist is a List<ObjectFilter> and contains the AttributeWiseMinMaxNormalization filter instance. Or you use the Parameterization API, which handles default values and instantiation.