On Mon, 20 Oct 2003 18:45:03 -0700, "albinali" <[EMAIL PROTECTED]> wrote:
> Hi all, > Thanks for the responses, I will try and explain the problem more clearly > using a different example: [ ... ] > .... The data set set collected from the space has > sensor readings along with the activities. Moreover, I want to construct a > bayesian network for every activity. Is this something I should know, 'What's a Bayesian network'? > Notice that if I include sensors that > are somehow linearly dependant, the bayesian network will get multiple > evidence from the same source, so thats why I would like to eliminate highly > correlated variables. The approach that I am using to tackle this problem, > is : Or, I can put it another way. You are implying you need to meet some difficult and unreasonable conditions in order to create a "bayesian network." Why create that? It is not enormously familiar to statisticians, to judge by the few hits from groups.google in the sci.stat.* groups. It is not familiar to me. However, I do note that there's a huge number of hits on the Web, and a *lot* more hits on comp.ai.* than sci.stat.* -- that seems to be a tool of the a.i. community, more than the statistical. You might post there. I was my impression, as I posted before, that you ought to learn more about what you are trying to measure, and figure out the *dimensions* and then some interval scores; so that regression tools will be applicable. Of course, regression tools are ones that I am familiar with. Hope this helps. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html "Taxes are the price we pay for civilization." . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
