Re: Is the Curt net a kind of decision tree?

Michael Olea <oleaj@xxxxxxxxxxxxx> wrote:
Curt Welch wrote:

Michael Olea <oleaj@xxxxxxxxxxxxx> wrote:
Curt Welch wrote:

Michael Olea <oleaj@xxxxxxxxxxxxx> wrote:
Curt Welch wrote:

But, and this is a big but, maximizing info throughput is not
really the issue. Isolating predictive info is the thing that
maximizes survival.

Well, this is why I put reinforcement learning at the top of the
list.

However, you seem to imply that isolating the predictive knowledge
in the signals is important by itself.

I think it's terrible, busting school children. Jail is no place for
children. They...

Uh, it's "busing" school children.

I don't get the point you are trying to make here.

It's a joke - a reference to an old SNL skit (I think). I'll give you a
more serious response later.

Yeah, that was my guess. I just don't know what the connection was. I
kept reading my response to see if I mis-read one of your words (aka
busting vs busing) or if I spelt something wrong with the same type of
error. I'll wait for your response.

But the response I'm most interested in is if you know of any technologies
that tell us how to transform signals to reduce correlations.

Is there some techniques from statistical analyses for doing this in some
domains? The normal approach in statistics is to take given signals
(variables), and analyze them for "meaning" vs any attempt to transform the
data into different data. But I wouldn't be surprised if this was some
large sub-field of statistics that I just don't know anything about.

And then there's the question of whether information theory tells us how to
do this. I know about Huffman coding which is the generally the type of
direction I'm talking about, but it's application is very narrow and
precise and doesn't directly address the level of problem I'm talking
about. But are there more advanced systems I don't know about?

--
Curt Welch http://CurtWelch.Com/
curt@xxxxxxxx http://NewsReader.Com/
.

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