"The goal of logic regression is to find predictors that are Boolean (logical) combinations of the original predictors", which might be more like what I need.
The rf's variable importance evaluations and oob might help feature selection but not feature construction, which is more of my concern. Thanks for any further suggestion or explanation. On 4/7/06, Sean Davis <[EMAIL PROTECTED]> wrote: > > Weiwei, > > You could also look into using one of several methods of "classification" > that calculate the "weight" of individual predictors in producing a > correct > result based on some version of cross-validation. One that I use > relatively > often is randomForest (in the randomForest package). > > Sean > > > > On 4/7/06 12:34 PM, "Peter Ehlers" <[EMAIL PROTECTED]> wrote: > > > It sounds as though 'logic regression' might help. See > > > > Ruczinski I, Kooperberg C, LeBlanc ML (2003). Logic Regression, > > Journal of Computational and Graphical Statistics, 12, 475-511. > > > > and the LogicReg package. > > > > Peter Ehlers > > > > Weiwei Shi wrote: > > > >> Hi there, > >> I have a statistics question on a classification problem: > >> > >> Suppose I have 1000 binary variables and one binary dependent variable. > I > >> want to find a way similar to PCA, in which I can find a couple of > >> combinations of those variables to discriminate best according to the > >> dependent variable. It is not only for dimension reduction, but more > >> important, for finding best way to construct features. This is NOT CDA > since > >> the explanatory variables are NOT continuous. I knew the existence of > that > >> method since I consulted before with a professor but I forgot the name > of > >> the method.. sigh... > >> > >> I am also wondering if R has already some function or package > addressing > >> this kind of problem. > >> > >> Thanks > >> > >> -- > >> Weiwei Shi, Ph.D > >> > >> "Did you always know?" > >> "No, I did not. But I believed..." > >> ---Matrix III > >> > >> [[alternative HTML version deleted]] > >> > >> ______________________________________________ > >> [email protected] mailing list > >> https://stat.ethz.ch/mailman/listinfo/r-help > >> PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > > > ______________________________________________ > > [email protected] mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > -- Weiwei Shi, Ph.D "Did you always know?" "No, I did not. But I believed..." ---Matrix III [[alternative HTML version deleted]] ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
