Old Categorisation Results
- Ten years or so ago, we used single net topologies to learn categories
(Information Retrieval and the congressional voting task).
This had the advantage of all the relevant neurons being
stimulated by the environment.
- Here's part of a neural simulation that learns irises. It
got about 93%, which is a reasonable score on this task.
- The picture shows the net during training.
- Blue circles are firing neurons, and the white squares are
neurons that don't fire in this cycle.
- One instance of an iris is presented in the base net, and
its told its category three (both by externally activating
those neurons).
- The firing in the middle two subnets is via spread of activation
emerging from learning.
- This is old work, and similar nets were used to categorise
yeast (52%), and other tasks.
- It's pretty general.
- What we'd like is the correct category neurons firing
for an input.
