Last updated: 2019-01-08 09:09:31 +0000
Upstream URL: git clone http://chriswarbo.net/git/tree-features.git
Contents of README follows
Generic feature extraction from XML documents.
For machine learning problems, we often need our inputs to be the same, fixed size. When we have a recursive structure, like a tree, we can fold over the structure to obtain a single value.
This is a very basic implementation of this idea: we take arbitrary XML documents, which are tree structured, and assign each element a value based on the md5 of its name and attributes concatenated together. We fold sub-trees together using bitwise circular convolution, to obtain a value for the whole tree.
Circular convolution is a linear operation, so it can’t preserve as much information as, for example, auto-encoding, but it is reasonably fast, requires no learning and is largely non-commutative/associative, so sub-trees should be distinguishable to a certain extent.