Hi all, as part of a corpus study I’m interested in using clustering techniques to group observations. Thanks to another discussion here I came across VNC as a possible technique for this.
~/Downloads/diachronic-text-analysis-master/HACluster/dendrogram.py in ete_tree(self, labels) 140 from ete2 import Tree, NodeStyle, TreeStyle 141 elif sys.version_info == 3: --> 142 from ete3 import Tree, NodeStyle, TreeStyle 143 else: 144 raise ValueError('Your version of Python is not supported.') ModuleNotFoundError: No module named 'ete3'
a) If anyone has any thoughts on this problem (what version of python was this written in?)
b) Knows of any related code that does similar stuff (excepting @mike.kestemont’s code for his Beckett project)?
c) More broadly whether anyone has particular opinions on this topic of style-based clustering? Obviously developing chronologically contiguous clusters is helpful on one level but hardly exhaustive, and I wonder what techniques others have used? I’ve employed some basic K-Means (although this often ends up producing chronologically contiguous clusters if corpus position is a variable) but not much beyond that.