I created an algorithm which works on categorical attributes. The input data comes with categorical attributes, but numerical ones as well.How can I apply a pre-processing which transforms the numerical attributes into categorical ones, in clever ways:the number of categories can adapt to the distribution of numerical values-> for example if there are 100 values, 99 of them grouped in a small range, and one clear outlier, then 2 categories should be created.the cutoff between categories should do its best to avoid that two close values are in different categories.-> for example, it is annoying that for 2 numerical values ranging from 0 to 100, a cutoff at 50 leaves values 49 and 51 in 2 different categories.Is there a field in computer science which deals with these issues? If there is an algorithm, is it pre-implemented in any language?
Looking for an algo transforming numerical attributes into categorical attributes -cleverly
clustering;categorical data;unsupervised learning