search for: prnn

In the help for rpart it says, "This differs from the tree function mainly in its handling of surrogate variables." And it says that an rpart object is a superset of a tree object. Both cite Brieman et al. 1984. Both call external code which looks like martian poetry to me. I've seen posts in the archives where BDR, and other knowledgeable folks, have said that rpart() is to be

Hello, Just a quick question about ppr in library modreg. I have looked at Ripley and Venables 2002 and it says that projection pursuit works "by projecting X in M carefully chosen directions" I want to know how it choses the directions? I presume it moves around the high-dimensional space of unit vectors finding ones that separate the response variables, but how. I looked at the

Hi, Just wonder if someone could comment on using linear discriminant analysis (LDA) vs. multinomial logistic regression in multi-class classification/prediction (nomial dependent variable, not ordinal)? What kind of difference in results can I expect from the 2 methods, which is better or more appropriate, or under what condiditon should I used one instead of the other? And is there other

I've been asked about "Canonical Variance Analysis" (CVA). I don't see any reference to it searching the R site. Does it go by other names? Genstat describes it thus: Canonical variates analysis operates on a within-group sums of squares and products matrix, calculated from a set of variates and factor that specifies the grouping of units. It finds linear combinations of the

Dear R people, I was recently reading the book `Classification and Regression Trees' by Breiman. This book talks about the CART program. Both Splus and R have implementations of this. However, the book talks about the possibility of extending the existing `standard' set of questions (for continuous variables, these are of the form X < c where X is the variable, c some const) to

Dear All, I'm classifying some data with various methods (binary classification). I'm interpreting the results via a confusion matrix from which I calculate the sensitifity and the fdr. The classifiers are trained on 575 data points and my test set has 50 data points. I'd like to calculate p-values for obtaining <=fdr and >=sensitifity for each classifier. I was thinking about

Hi, Having dipped my toe into R a few times over the last year or two, in the last few weeks I've been using it more and more; I'm now a thorough convert. I've just joined the list, because although it's great, I do have this problem... I'm using linear discriminant analysis for binary classification, and am happy with the classification performance using predict(). What

At 06:09 AM 5/1/00 +0100, Prof Brian D Ripley wrote: >On Sun, 30 Apr 2000, Stephen R. Laniel wrote: > >> I was just now surprised to note that functions to go generalized additive >> models don't appear to exist under R 1.000. In particular, the gam() and >> loess() functions aren't there. Are they hidden somewhere and I just >> haven't noticed? >

Hi all, Say I have a matrix A with dimension m x 2 and matrix B with dimension n x 2. I would like to find the row in A that is closest to the each row in B. Here's an example (using a loop): set.seed(1) A <- matrix(runif(12), 6, 2) # 6 x 2 B <- matrix(runif(6), 3, 2) # 3 x 2 m <- vector("numeric", nrow(B)) for(j in 1:nrow(B)) { d <- (A[, 1] - B[j, 1])^2 + (A[,

Hi, I'm running gam (mgcv version 1.3-29) and glm (logit) (stats R 2.61) on the same models/data, and I got error messages for the gam() model and warnings for the glm() model. R-help suggested that the glm() warning messages are due to the model perfectly predicting binary output. Perhaps the model overfits the data? I inspected my data and it was not immediately obvious to me (though I