[wplug] OT: AI

[Chris]

> -----Original Message----- 
> Behalf Of Devin Lee Drew
> 
> On Apr 29, 2004, at 9:53 AM, Bill Moran wrote:
> 
> > Patrick Weber wrote:
> >> You may find that the topic of Genetic Algorithms may interest you.
> >> They
> >> have long been a topic of AI research and have some fun aspects to 
> >> them.
> >> Basically what GA's do is take a series of parameters and "mutate" 
> >> them to
> >> use the biological term.  Then it "breeds" these 
> parameters to produce
> >> outcomes.  The outcomes that most closely resemble what 
> you want are 
> >> then
> >> selected, mutated and bred again.  What this does is "evolve" your
> >> parameters for your data in a similar way that monkeys evolve into 
> >> people.
> >
> > <humor>
> > If humans evolved from monkeys, why are there still 
> monkeys? </humor>
> 
> It is a niche. We're still around because someone needs to write code.
> ;)
> 
> Regardless of how amazing the 'AI' is, you're still going to benefit 
> from an understanding of the model that it provides. A genetic 
> algorithm might give you a confusing combination of functions when a 
> simpler model might fit the data. I'd say you should explore all 
> possibilities. What do you mean by 'regressions' Chris?
> 

http://tinyurl.com/2jt3w

"a graph of the mathematical relationship between two variables."
"a smooth curve fitted to the set of paired data in regression analysis"

After some more reading, I think the "area" that I need to look into is Data
Mining.  That seems to fit my situation the best.

Thanks everyone for you help.  I think that this is one of the most helpful
lists that I've seen.

Chris Romano