similar to: about usage of weights in nnet

======= At 2005-07-22, 12:56:12 you wrote: ======= >On Fri, 22 Jul 2005, Baoqiang Cao wrote: > >> Dear All, >> >> I have such a two-class problem, one class is very large(~98% of total), >> and the other is just 2%. According to manual of nnet, I need setup >> "weights", so I intend to set 1 for class one, 49 for class 2. How do I >> do that?

Dear All, I have such a two-class problem, one class is very large(~98% of total), and the other is just 2%. According to manual of nnet, I need setup "weights", so I intend to set 1 for class one, 49 for class 2. How do I do that? Just weights=49? Meanwhile I'd like to try svm(e1071), again, how do I setup "class.weights"? Thanks. BTW: Many thanks to Jake and Uwe for

One possibility is to look at predict.nnet(), and - Write an R function that write out parts of an nnet object that are needed by predict.nnet() to an external file. - Re-write predict.nnet() in C, reading the model information from the external file. Obviously you'll also need the C source for the code that predict.nnet() calls, and modify those as needed to strip out dependency on R, if

Dear All, I'm learning to train a neural network with my training data by using nnet package, then evaluate it with a evaluation set. My problem here is that, I need the trained network to be used in future, so, what should I store? and How? Any other options other than nnet package? Any example will be highly appreciated! Best, Baoqiang Cao

Dear All, After followed the help of nnet, I could get the networks trained and, excitedly, get the prediction for other samples. It is a two classes data set, I used "N" and "P" to label the two. My question is, how do I get the predicted numerical value for each sample? Not just give me the label(either "N" or "P")? Thanks! FYI: The nnet example I

Dear All, I have a data, suppose it is an N*M matrix data. All I want is to classify it into, let see, 3 classes. Which method(s) do you think is(are) appropriate for this purpose? Any reference will be welcome! Thanks! Best, Baoqiang Cao

Dear All, I am producing a figure with many curves on it. How do I make the legends for all those curves smaller so that it can fit the figure itself? The commands I used for ploting are: plot(x1,y1,col=1,lty=1) lines(x2,y2,col=2,lty=2) ... legend(0.3,0.4,c("name1","name2",...),col=1:20,lty=1:20) Any tips for making the legend fit the figure will very welcome! Thanks! Best,

Dear All, I tried to plot a variety of lines(curves) on same figure. What I did is, plot(x=x1,y=y1) lines(x=x2,y=y2) lines(x=x3,y=y3) ... In my data, the maximum of y1 is much smaller than those maximums of other y vectors. So, in the figure I got, there are some curves which are not complete, I mean, they were cut off at the maximum of y1 at the y axis. Could anybody point out some right

Dear All, I am using wilcox.test to test two samples, data_a and data_b, earch sample has 3 replicates, suppose data_a and data_b are 20*3 matrix. Then I used the following to test the null hypothesis (they are from same distribution.): wilcox.test(x=data_a, y=data_b, alternative="g") I got pvalue = 1.90806170863311e-09. When I switched data_a and data_b by doing the following:

Hi Everyone, I'm trying to use cutree to get the clusters after hclust. What I used is: mycluster<-cutree(cnclust,h=0.5) Now, my problem is, how can I get the actual clusters? Thanks! Best, Baoqiang Cao

Dear All, Just start to use the long expected R, my focus will be doing clustering on microarray data, just wonder, anyone can show me any references to conquer the steep learning curve? Thanks! Best regards, Baoqiang Cao

Hi there, I really couldn't find out how to plot histogram with point/line instead of rectangle for each bin? Any help please? Thanks! Best, -Cao

I am using library(nnet) to train up an ANN with what I believe is a moderately sized dataset, but R is complaining about too many weights: --- > nn.1 <- nnet(t(data), targets, size = 4, rang = 0.1, decay = 5e-4, maxit = 200) Error in nnet.default(t(data), targets, size = 4, rang = 0.1, decay = 5e-04, : Too many (1614) weights > dim(targets) [1] 146 2 > dim(data) ## Note

Dear R-users, dear Prof. Ripley as package maintainer I tried to investigate the odd error, when I call nnet together with a 'weights' parameter, using the 'fgl' example in V&R p 348 The error I get is: Error in eval(expr, envir, enclos) : Object "w" not found I think it is a kind of scoping problem, but I really cannot see, what the problem exactly is. and

Dear R-users I use nnet for a classification (2 classes) problem. I use the code CVnn1, CVnn2 as described in V&R. The thing I changed to the code is: I define the (class) weight for each observation in each cv 'bag' and give the vector of weights as parameter of nnet(..weights = weight.vector...) Unfortunately I get an error during some (but not all!) inner-fold cv runs:

Hi everybody, I want to obtain a classification model using the nnet function for a simple two class problem. My problem is that number of samples in the first class (n1) is about twice higher than the one in class two (n2). I would like to use the weights argument in the nnet function to equalize the prior probabilities, but I am not sure which values I should assign. My first guess would be

Dear All, I was trying to format a numeric vector (100*1) by using outd <- format(x=m, sci=F, digits=2) > outd[1:10] [1] " 0.01787758" "-0.14760306" "-0.45806041" "-0.67858525" "-0.64591748" [6] "-0.05918100" "-0.25632276" "-0.15980138" "-0.08359873" "-0.37866688" >m[1:10] [1]

Hi, I have a question about using lm on matrix, have to admit it is very trivial but I just couldn't find the answer after searched the mailing list and other online tutorial. It would be great if you could help. I have a matrix "trainx" of 492(rows) by 220(columns) that is my x, and trainy is 492 by 1. Also, I have the newdata testx which is 240 (rows) by 220 (columns). Here is

Hi, I'm trying to plot something in the following way and would like if you could help: I'd like in a same plot window, two plots are shown, the left one is a bird-view plot of the whole data, the right half keep changing, i.e., different plots will be shown up on request, so that when I select/click on some where in the left plot, the right plot will be the corresponding plot. What I

Hello Guys, I'm using the package RankProduct to determine the differential expression of genes in 2 classes. The importance of the thing is to know: - How can I determine which class is the class of up-regulated genes and which to the down regulated gene - How can i interpret the results : $pfp, $RPs, $RPrank, Orirank,