I have medical data with max value 500 along with values like age and binary values for sex (0 or 1). I will use clustering to find the number of clusters. Which is the best approach among three.Normalize each coloumn,standardize with z scores or do nothing. For z-scores i heard that he data should be a normal distribution,so should i box- cox them first? Any help is appreciated
You should either do Normalization or standardization. You cannot do clustering properly with mixed attributes (continuous and binary) without the features scaling. You can check the following link as well: Is it important to scale data before clustering?
$\begingroup$ and i have to standardize every coloumn separated ,right? $\endgroup$ Aug 1, 2017 at 21:56
$\begingroup$ Yes, that should be the way. $\endgroup$ Aug 1, 2017 at 22:05
If you use Z-scores you should first be sure there is no outside standard population for converting them to z-scores. For example, children's height and weight are sometimes converted to z-scores, but researchers use the World Health Organization (WHO) dataset to do this, so the computed Z-score result is where each subject in the researcher's datatset would fall on the WHO distribution, if they were a member of that distribution.