similar to: interpretation of svm models with the e1071 package

Dear all, I am currently looking for a book about support vector machines for regression and classification and am a bit lost since they are plenty of books dealing with this subject. I am not totally new to the field and would like to get more information on that subject for later use with the e1071 <http://cran.r-project.org/web/packages/e1071/index.html> package for instance. Does

R-helpers, Beginner in R language, I have a problem to install a package (multiv) in R for Windows 98 (R-Gui) First I have got the multiv.zip file from the CRAN precompiled contributed packages for Windows and put this file in C:/Program Files/rw1022. in R-Gui I tried to install it as following > install.packages("C:/Program Files/rw1022/multiv.zip") I received the following

Dera R helpers, I have a (x,y,z) data file where x and y are spatial coordinates and z a variable. I have some missing values in the z column and I would like to replace them with an optimized estimation from the neighbour cells. I could not find any function in R to do that. Is anybody aware of such function ? Maybe someone knows how to implement the Papadakis method in R... Thanks for your

Dear r-helpers, Prior to analysis of variance, I ran the Boxcox function (MASS library) to find the best power transformation of my data. However, reading the Boxcox help file, I cannot figure out if this function (through its associated log-likelihood function) corrects for * normality only * or if it also induces * homogeneity of variances *. I found in Biometry (Sokal and Rohlf, p. 419)

Hello to the R people, within ward clustering the distance calculated to decide the clustering of 2 subsets (h1 and h2) is the variation of inertia : d(h1,h2)=I(h1Uh2)-I(h1)-I(h2); i've been said that a way to calculate faster this d(h1,h2) is using the huygens theorem decomposing the inertia into "the inertia to the centroid + the distance to an axe" (that's my version ...). My

Hello to the R community, which dataset(s) available in R is suitable to test the quality of a classification tool ? Thansk in advance, -- Nicolas Baurin Doctorant Institut de Chimie Organique et Analytique, UPRES-A 6005 http://www.univ-orleans.fr/SCIENCES/ICOA/ Universit? d'Orl?ans, BP 6759 45067 ORLEANS Cedex 2, France Tel: (33+) 2 38 49 45 77

Hi R people, i'm looking for the Reciprocal Nearest Neighbour algorithm applied to Ward clustering; I know that it is explained in details in the following book: Downs, G. M.; Willett, P. In Advanced Computer-Assisted Techniques in Drug Discovery; van de Waterbeemd, H., Ed.; VCH: Weinheim, 1994; Vol. 3. but cannot order copies it without knowing the pages involved; could someone

Hello to all R people, for the application of a function to each column of a matrix (ex: function sum()), i'd like to know if there is a simpler (and faster) alternative to a loop like : for (i in 1: ncol(m)){sum(m[i])} Thanks in advance, Cordialement, -- Nicolas Baurin Doctorant Institut de Chimie Organique et Analytique, UPRES-A 6005 Universit? d'Orl?ans, BP 6759 45067 ORLEANS Cedex

Hello all. I have just installed R version 1.6.1 for Windows on a XP machine. I would like to use R in batch mode. For this, I looked for Rcmd.exe, but did not find it. Any hint where it could be? (in version 1.4.1, it was in the bin directory...) Fr?d?ric Darboux ....................................................... INRA Orl?ans - Science du Sol Avenue de la Pomme de Pin BP 20619 F-45166

Hello, i'm looking for the procedure to generate a random number between 0-1. Try rnorm() but can't get to do generate between 0-1 thanks(i'm sur it's easy) -- Nicolas Baurin Doctorant Institut de Chimie Organique et Analytique, UPRES-A 6005 Universit? d'Orl?ans, BP 6759 45067 ORLEANS Cedex 2, France Tel: (33+) 2 38 49 45 77

Hello R people, i'm trying to implement the Partial Least Squares algorithm called SAMPLS from "J.Comp-Aided Molecular Design", 7 (1993), 587-619. It's faster than the classical PLS algorithm for fat matrix (m>>n). Here's the algorithm from the article of Bush B. L. and Nachbar R.B.: X is the matrix of explanatories proprieties (m*n) , y the matrix of responses, h

Dear R-Users! I am using the svm function (e1071 package) to classify two groups using a set of 180 indicator variables. Now I am confused about the cross-validation procedure. (A) On one hand I use the setting cross=10 in the svm function to run 10 cross-validation iterations and to get an estimate of the svm's performance in prediction. (B) On the other hand most tutorials I found

Hello, I have an SVM model previously calibrated using libsvm R implementation from the e1071 package. I would like to use this SVM to predict values, from a Java program. I first tried to use jlibsvm and the "standard" java implementation of libsvm, without success. Thus, I am now considering writing data in files from my Java code, calling an R program to predict values, then gather

Hello to all of you, What i try to do : i got data of the type (x,y) which i plot with plot (x,y). i want to actualise that plot adding new points (x,y) (i did it with points(x,y)): how can i adjust the scale of the axis x and y to see all the points in the window. Ex: i start with plot (1,0.5). If i do points(0.8,0.5) no problem, all my points are visible on the graph. But if i do points(2,2),

Hello, As far I saw in archive mailing list, I am not the first person with this problem. Anyway I was not able to pass this error once the information I got from the archive it is not very conclusive for this case. I have used linear, radial and sigmoid kernels for the same data in the same conditions and everything is ok. This problem just happens with the polynomial kernel. I send the

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Hi, I run the following tuning function for svm. It's very strange that every time i run this function, the best.parameters give different values. [A] >svm.tune <- tune(svm, train.x, train.y, validation.x=train.x, validation.y=train.y, ranges = list(gamma = 2^(-1:2), cost = 2^(-3:2))) # where train.x and train.y are matrix

Dear All , 1- I'm trying to access the values of fitted(model) after model<- tune.svm( ) but seemingly it is not poosible. How can I access to values of fitted ? However ,it is possible only after model<- svm( ) 2- How can I access to the other values such as the number of Support Vectors , gamma, cost , nu , epsilon , after model<- tune.svm( ) ? these are not possible? I

I am starting to use svm from e1071 and I wonder how exactly crossvalidation is implemented. Whenever I run > svm.model <- svm(y ~ ., data = trainset, cross = 3) on my data I get dirrerent values for svm.model$MSE e.g. [1] 0.9517001 1.7069627 0.6108726 [1] 0.3634670 0.9165497 1.4606322 This suggests to me that data are scrambled each time - the last time I looked at libsvm python

Hi, I am trying to use tune.svm in e1071 package. the command i use is tobj <- tune.svm(labels, data= data, cost = 10^(1:2)) Should the last column of the 'data' contain the labels as well? I want to use the linear kernel. But it gives me the error "Error in model.frame.default(formula, data) : 'data' must be a data.frame, not a matrix or an array" Do you know why