newlispfanclub.alh.net

Hi,

With (bayes-train) it is possible to train lists and put this into a context. As is described in the documentation, the syntax is (bayes-train list-M1 list-M2 [list-M3 ... ] sym-context-D), where the lists are the categories to be trained.

What I want to do is train an additional list into the same context.

One way of doing this, is reserve the position for it: (bayes-train c1 c2 '() '() '() 'MYCONTEXT) . Here 3 positions have been reserved which I can update later on in my program.

However, if I have used all positions and want to add another category, how should I do that? I want to do this dynamically, I mean, without interruption of the running program. So stopping, changing the code, and starting is not an option.

In case of self-learning program this seems to be a very convenient construction. While I am encountering new categories, I can add them on the fly. Is there a way of doing this?

Peter

You could append a new empty category with 0's this way:
You simply push a 0 at the end of each list contained in the symbols. After this you keep on training with 3 categories. If you are out of data for the first category, just populate only the 3rd list:
Lutz

Thanks!

How do I change the (bayes-train) command then? Do I need to interact manually with the sourcefile to adapt it to the new amount of categories? Or should I do this with a (case) and write down all possibilities? Still I am limited to the amount of possibilities I put into my sourcefile then.

Also, is there a limit on the amount of categories?

Peter

There is no limit to the amount of categories you could train.

you would have to change the 'bayes-train' statements to accomodate more categories.

Perhaps as a workaround you can train from the beginning with a fixed max amount of categories and leave unused categories with '() empty lists. In-between training sessions you can save the context then load it again later using 'save' and 'load' for contexts.

Lutz

Thank you for your clarifications!

Peter