I would like to classify individuals of a database by a single quantitative variable. Is hierachical clustering suitable to do this? If it is possible, how the algorithm work? If use hierachical clustering is not right, which other procedures or techniques could I use? My purpose is not classify the variable, but individuals. So decision trees are not suitable.
You could order the nob values from low to high and then use a search procedure to identify when and if local mean(s) changed significantly via Intervention Detection (trial and error). ID is esseentially a single dimension(characteristic) cluster analysis. Alternatively you could pre-specify the number of groups (classes) that you wished to have(n) and then find the n-1 breakpoints which optimally classifies the nob values. I have not ever done this but it might be worth a try.