similar to: plot SVM

I run the following code, all other is ok, but plot(m.svm,p5.new,As~Cur) is not ok Anyone know why? install.packages("e1071") library(e1071) library(MASS) p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") p5.new<-subset(p5,select=-Ms) p5.new$Y<-factor(p5.new$Y) levels(p5.new$Y) <- list(Out=c(1), In=c(0)) attach(p5.new)

I run the following code, all other is ok, but plot(m.svm,p5.new,As~Cur) is not ok Anyone know why? install.packages("e1071") library(e1071) library(MASS) p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") p5.new<-subset(p5,select=-Ms) p5.new$Y<-factor(p5.new$Y) levels(p5.new$Y) <- list(Out=c(1), In=c(0)) attach(p5.new)

> install.packages("e1071") Warning: package 'e1071' is in use and will not be installed > library(e1071) > library(MASS) > p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") > attach(p5) The following object(s) are masked from p5 ( position 3 ) : Aa As Cur Ms P Y The following object(s) are

I am trying to fit a logistic regression model for this data set. Firstly, I want to plot P(Y=1) vs As and P(Y=1) vs Aa. Does any body know how to do these in R. Thanks, Aimin > p5 <- read.csv("http://www.public.iastate.edu/~aiminy/data/p_5_2.csv") > str(p5) 'data.frame': 1030 obs. of 6 variables: $ P : Factor w/ 5 levels "821p","8ABP",..: 1

I have a dataset like this: p aa index x y z sdx sdy sdz delta as ms cur sc 1 821p MET 1 -5.09688 32.8830 -5.857620 1.478200 1.73998 0.825778 13.7883 126.91 92.37 -0.1320180 111.0990 2 821p THR 2 -4.07357 28.6881 -4.838430 0.597674 1.37860 1.165780 13.7207 64.09 50.72 -0.0977129 98.5319 3 821p GLU 3 -5.86733 30.4759

I have a data set like this I want to assign "outward" to Y if sc <90 and assign "inward" to Y if sc>=90. then cbind(p1982,Y) to get like these p aa as ms cur sc Y 1 154l_aa ARG 152.04 108.83 -0.1020140 92.10410 inward 2 154l_aa THR 15.86 28.32 0.2563560 103.67100 inward 3 154l_aa ASP 65.13 59.16 0.0312137 7.27311 outward 4 154l_aa CYS 57.20 49.85

I use tune.svm to tune gamma and cost for my training dataset. I use PC, it runs very slowly. Does anyone know how to make it faster? Aimin

Having a classification problem, I am using SVM for prediction in R. In dataset, there are integer as well as categorical variables. I got error while predicting with predict method. svp3c <- ksvm(input_dataset3$isCRgt3~., data=input_dataset3,type="C-svc") p3<-predict(svp3c,newdata=input_dataset_prediction[,-1],type="response") error :: Error in

Dear Sir, I got a problem with my program. I would like to classify my data using bagging support vector machine ensemble. I split my data into training data and test data. For a given data sets TR(X), K replicated training data sets are first randomly generated by bootstrapping technique with replacement. Next, Support Vector Mechine (SVM) is applied for each bootstrap data sets. Finally, the

I have a data(ABC) like this: x y A 3 4 A 1 3 B 2 6 B 4 8 C 5 4 C 6 7 I want to split this data into A: x y A 3 4 A 1 3 B B 2 6 B 4 8 C C 5 4 C 6 7 anyone knows how to do that? thanks, Aimin Yan

Hello, I use nnet to do prediction for a continuous variable. after that, I calculate correlation coefficient between predicted value and real observation. I run my code(see following) several time, but I get different correlation coefficient each time. Anyone know why? In addition, How to calculate prediction accuracy for prediction of continuous variable? Aimin thanks, > m.nn.omega

> > So i guess from your prev. email the svmModel$coefs correspond to the > "Alpha" . yes (times the sign of y!). > > Why do I see three columns in the coefs?( Is this the number of classes -1 > = Numbe of hyperplanes) yes, but in a packed format which is not trivial. I attach some explanation I sent to R-help some time ago (the guy wanted to write his own

I have a question in R. In directory H:/Delta_angle I have 19 files like this: ALA.delta ASN.delta ASP.delta CYS.delta GLN.delta GLU.delta HIS.delta ILE.delta LEU.delta LYS.delta MET.delta PHE.delta PRO.delta SER.delta THR.delta TRP.delta TYR.delta VAL.delta I want to read these files to 19 data sets in R. All these data sets have "P","AA",index","delta"

1. This is _not_ a bug in R itself. Please don't use R's bug reporting system for contributed packages. 2. This is _not_ a bug in svm() in `e1071'. I believe you forgot to take sqrt. 3. You really should use the `tot.MSE' component rather than the mean of the `MSE' component, but this is only a very small difference. So, instead of spread[i] <- mean(mysvm$MSE), you

Full_Name: Noel O'Boyle Version: 2.1.0 OS: Debian GNU/Linux Sarge Submission from: (NULL) (131.111.8.96) (1) Description of error The 10-fold CV option for the svm function in e1071 appears to give incorrect results for the rmse. The example code in (3) uses the example regression data in the svm documentation. The rmse for internal prediction is 0.24. It is expected the 10-fold CV rmse

Hello! We are new in using R. We use the SVM module from the library ''e1071'' for training. Problem formulation: a classification has been performed using SVM module (linear kernel). Later, a new data set (test set) comparable to the training data shall be scaled in the same way as the training set (using the same scaling parameter set, but without using the SVM again

I am using the "predict" function on a support vector machine (svm) object, and I don't understand why I can't predict on a dataset with more observations than the training dataset. I think this problem is a generic "predict" problem, but I'm not sure. The original svm was fit on 50 observations.

Hello, When calling several times the svm() function, I get different results. Do I miss something, or is there some random generation in the C library? In this second hypothesis, is it possible to fix an eventual seed? Thank you Pierre ### Example library('e1071') x = rnorm(100) # train set y = rnorm(100) c = runif(100)>0.5 x2 = rnorm(100)# test set y2 = rnorm(100) # learning a

I try Sweave and get Sweave-test-1.tex but hot to run LaTeX on 'Sweave-test-1.tex'? I am using WinEdt. thanks, Aimin > Sweave(testfile) Writing to file Sweave-test-1.tex Processing code chunks ... 1 : print term verbatim 2 : term hide 3 : echo print term verbatim 4 : term verbatim 5 : echo term verbatim 6 : echo term verbatim eps pdf 7 : echo term verbatim eps pdf

Hi, I have some difficulties in interpreting the prediction of a svm model using the package e1071. y1 is the variable I want to predict. It is of type factor and has got two levels: "< 50%" and "> 50%". z is the dataset. > model <- svm(y1 ~ ., data = z,type="C-classification", cross=10) > model Call: svm(formula = y1 ~ ., data = z, type =