Subject: Re: ML for MI
My primary concern with all of this was brought out by Loren Cobb back in 2000.

To me, all of this thunder and lightning about datamining seems to miss the point. Datamining works as a concept only within the impoverished world of statistical models. Outside of that domain there are gorgeously complex mathematical models whose validity derives from well-understood mechanisms of cause and effect. When causation is poorly understood, as for example in the stock market, then our models are necessarily simpler and more ad hoc, and the cry of Datamining! has at least some semblance of applicability. But is it helpful? I think not. We need better models of cause and effect, not purer statistics.

http://www.datahelper.com/mi/s...

The question then is: How do you insure using approaches such as this that there is truly a reasonable cause/effect relationship going on?