I'm intending to make a cluster analysis of 100 objects. I've read a couple of books and determined that a Hierarchical agglomerative procedure with Ward's linkage method should be used in my case. As for the distance measure between objects, I am choosing the Euclidean distance.
The problem, however, is that in the books, these distance measures are performed using a maximum of 3 variables per object. In some papers, I have found research that uses 6 variables per object, but that's it. My objects have 114 variables each.
My question is the following: Is there a maximum number of variables per object that a distance measurement can work with?
Some insight into the nature of my objects: Each object has 6 different sets of 19 variables, every set has the same nature, but are different between each other. Every one of the 114 (6x19) variables is a float number between -1 and 1.
If 114 are indeed above the maximum, is there a tool or a procedure that I am missing that could help me perform the cluster analysis given the nature of my objects? Maybe group them into subsets before clustering?
Any help is appreciated. Maybe a book or research I can read on the topic.