search for: mse

...amma*u'*v + coef0)^degree It would seem that polynomial kernel with gamma = 1; coef0 = 0 and degree = 1 should be identical to linear kernel, however it gives me significantly different results for very simple data set, with linear kernel significantly outperforming polynomial kernel. *** mse, r2 = 0.5, 0.9 for linear *** mse, r2 = 1.8, 0.1 for polynomial What am I missing ? Ryszard P.S. Here are my results: # simple cross validation function cv.svm <- function(formula, data, ntry = 3, kernel = "linear", scale = FALSE, cross = 3, gamma = 1/(dim(data...

...feature). It's related to the --keep-dirlinks option, when combined with --delete . I have the following directory structure on server A: ls -lR software software: total 238 drwxr-xr-x 2 biolord bioinf 1024 Sep 20 10:49 EMBOSS/ lrwxrwxrwx 1 biolord bioinf 6 Feb 5 2003 MSE -> EMBOSS/ lrwxrwxrwx 1 biolord bioinf 6 Feb 5 2003 PHYLIP -> EMBOSS/ ... lrwxrwxrwx 1 biolord bioinf 6 Feb 5 2003 TOPO -> EMBOSS/ ... software/EMBOSS: total 87942 -rw-r--r-- 1 biolord bioinf 551090 Jul 15 18:54 DOMAINATRIX-1.0.0.tar.gz -rw-r--r-- 1 biol...

Dear R-experts, Here below my R code with an error message. Can somebody help me to fix this error?? Really appreciate your help. Best, ############################################################ #?MSE CROSSVALIDATION Lasso regression? library(glmnet) ? x1=c(34,35,12,13,15,37,65,45,47,67,87,45,46,39,87,98,67,51,10,30,65,34,57,68,98,86,45,65,34,78,98,123,202,231,154,21,34,26,56,78,99,83,46,58,91) x2=c(1,3,2,4,5,6,7,3,8,9,10,11,12,1,3,4,2,3,4,5,4,6,8,7,9,4,3,6,7,9,8,4,7,6,1,3,2,5,6,8,7,1,1,2,9) y...

I have the following function, a MSE calc based on some Multivariate normals: MV.MSE<-function(n,EP,X,S){ (dmvnorm(X,mean=rep(0,2),I+S+EP)-dmvnorm(X,mean=rep(0,2),I+S))^2 + 1/n*(dmvnorm(X,mean=rep(0,2),1+S+EP/2)*det(4*pi*EP)^-.5- (dmvnorm(X,mean=rep(0,2),I+S+EP ))^2)} I can get the MV.MSE for given v...

...1 0.0415065 but when I wrote the following lines: summary(greeneSur) I obtained the following results: systemfit results method: SUR N DF SSR detRCov OLS-R2 McElroy-R2 system 100 85 347048 1.39234e+14 0.844042 0.868682 N DF SSR MSE RMSE R2 Adj R2 Chrysler 20 17 3056.98 179.823 13.4098 0.911862 0.901493 General.Electric 20 17 14009.12 824.066 28.7065 0.687636 0.650887 General.Motors 20 17 144320.88 8489.463 92.1383 0.920742 0.911417 US.Steel 20 17 183763.01 10809.589 103.9692 0.421959 0...

Dear R Users, My question is overall and not necessarily related to R. Suppose we face to a situation in which MSE( Mean Squared Error) shows desired results but Bias shows undesired ones, Or in advers. How can we evaluate the results. And suppose, Both MSE and Bias are important for us. The ecact question is that, whether there is any combined measure of two above metrics. Thank you so much for any repl...

Dear Random Forests gurus, I have a question about R^2 provided by randomForest (for regression). I don't succeed in finding this information. In the help file for randomForest under "Value" it says: rsq: (regression only) - "pseudo R-squared'': 1 - mse / Var(y). Could someone please explain in somewhat more detail how exactly R^2 is calculated? Is "mse" mean squared error for prediction? Is "mse" an average of mse's for all trees run on out-of-bag holdout samples? In other words - is this R^2 based on out-of-bag samples?...

...a via R-help <r-help at r-project.org> wrote: > > Dear R-experts, > > Here below my R code with an error message. Can somebody help me to fix this error? > Really appreciate your help. > > Best, > > ############################################################ > # MSE CROSSVALIDATION Lasso regression > > library(glmnet) > > > x1=c(34,35,12,13,15,37,65,45,47,67,87,45,46,39,87,98,67,51,10,30,65,34,57,68,98,86,45,65,34,78,98,123,202,231,154,21,34,26,56,78,99,83,46,58,91) > x2=c(1,3,2,4,5,6,7,3,8,9,10,11,12,1,3,4,2,3,4,5,4,6,8,7,9,4,3,6,7,9,8,4,7,6...

...res<-summary(aovFull)[[1]][,3] for (raterAct in 1:tt) { raterActCat<-raterLabels[raterAct] aovAct<-aov(Result~Subject,data=Frame1[Frame1$Rater==raterActCat,]) meanSquares<-c(meanSquares,summary(aovAct)[[1]][2,3]) } names(meanSquares)<-c('MSS','MSR','MSSR','MSE',paste('MSE',levels(Frame1$Rater),sep='')) MSS<-meanSquares[1] MSR<-meanSquares[2] MSSR<-meanSquares[3] MSE<-meanSquares[4] MSEpart<-meanSquares[-(1:4)] # the same for random and fixed, see table 2 (p. 780) and 3 (p. 281) sighat2Srandom<-(MSS-MSSR)/(mm*tt) sig...

Several ways: 1. Read ?randomForest, especially the `Value' section. 2. Look at str(myforest.rf). 3. Look at print.randomForest. If the forest has 100 trees, then the mse and rsq are vectors with 100 elements each, the i-th element being the mse (or rsq) of the forest consisting of the first i trees. So the last element is the mse (or rsq) of the whole forest. HTH, Andy > From: David L. Van Brunt, Ph.D. > > I'm almost embarrassed to ask... Almost! &...

Hi, I am trying to integrate a function which is approximately constant over the range of the integration. The function is as follows: > my.fcn = function(mu){ + m = 1000 + z = 0 + z.mse = 0 + for(i in 1:m){ + z[i] = rnorm(1, mu, 1) + z.mse = z.mse + (z[i] - mu)^2 + } + return(z.mse/m) + } > my.fcn(-10) [1] 1.021711 > my.fcn(10) [1] 0.9995235 > my.fcn(-5) [1] 1.012727 > my.fcn(5) [1] 1.033595 > my.fcn(0) [1] 1.106282 > The function takes the value (approx) 1 ove...

Hi, I am using nnet to learn transfer functions. For each transfer function I can estimate the best possible Mean Squared Error (MSE). So, rather than trying to grind the MSE to 0, I would like to use abstol to stop training once the best MSE is reached. Can anyone confirm that the abstol parameter in the nnet function is the MSE, or is it the Sum-of-Squares (SSE)? Best regards, Sam. [[alternative HTML version deleted]]

Dear useRs, I am working on a series of field experiments (159 in total) carried out in different years in several locations. The cultivars in each experiment are not always the same, in fact they change over time. I would like to get the fitted values and MSE of the individual fits from the following lmList object, so I can use them to fit a mixed model using the fitted values and weight each environment with (number of reps/MSE)/Average MSE. library(nlme) yield.list <- lmList(yield ~ as.factor(rep) + id | yearloc, data = df1, na.action = na.omit)...

...nction(pars,theta) { kappa<- pars[1]; mu<- pars[2]; IoK<- besselI(kappa, nu=0); res<- besselI(2*kappa, nu=0)/2/IoK^2 - mean(exp(kappa*cos(theta-mu)))/IoK; if(is.na(res)||is.infinite(res)){ print(pars); # assign("Theta", theta, env=.GlobalEnv); } return(res); } mse.Dk2<- function(pars, s, n) { sum.est <- SSE <- numeric(2); j<- 0; while(j<=n){ theta<- rvm(s, pi, k=pars[1]) - pi; est<- optim(par=pars, fn=Dk2, lower=c(0.001, -pi), upper=c(10, pi), method="L-BFGS-B", theta=theta); i<- 0; while(e...

Dear Researches, I am using RF (in regression way) for analize several metrics extract from image. I am tuning RF setting a loop using different range of mtry, tree and nodesize using the lower value of MSE-OOB mtry from 1 to 5 nodesize from1 to 10 tree from 1 to 500 using this paper as refery Palmer, D. S., O'Boyle, N. M., Glen, R. C., & Mitchell, J. B. O. (2007). Random Forest Models To Predict Aqueous Solubility. Journal of Chemical Information and Modeling, 47, 150-158. my problem is t...

...ormation about this error and possibly the source in the coding? 2). The results are saving successfully to a file as a list however, I wish to save the data into a matrix that resembles: Subset 1, Subset 2, Subset n, Var Importance: VI.1 VI.2 VI.n mse: mse.1 mse.2 mse.n rsq: rsq.1 rsq.2 rsq.n IV-1: x.1 x.2 x.n IV-2: y.1 y.2 y.n IV-n: n.1 a.2 n.n How cou...

...t;> ? ? ? >> >> Really appreciate your help. >> ? ? ? >> >> >> ? ? ? >> >> Best, >> ? ? ? >> >> >> ? ? ? >> >> ############################################################ >> ? ? ? >> >> # MSE CROSSVALIDATION Lasso regression >> ? ? ? >> >> >> ? ? ? >> >> library(glmnet) >> ? ? ? >> >> >> ? ? ? >> >> >> ? ? ? >> >> >> ? ? ? >> x1=c(34,35,12,13,15,37,65,45,47,67,87,45,46,39,87,98,67...

If possible I'd like to produce a function that applies a formula to a column in a matrix (essentially calculating the mse) and then inserts it between values of a an array ... confusing I know, here is an example of what I'm trying to accomplish: ## create a matrix (a <- matrix(c(3,6,4,8,5,9,12,15),nrow=4)) ## get the mean of all columns (b <- apply(a,2,mean)) ## calculate the mse of column 1 (c <- (sd(...

...llo - I am using glmnet to generate a model for multiple cohorts i. For each i, I run 5 separate models, each with a different x variable. I want to compare the fit statistic for each i and x combination. When I use auc, the output is in some cases is < .5 (.49). In addition, if I compare mean MSE (with upper and lower bounds) ... there is no difference across my various x variables, but mean AUC (with upper and lower bounds) shows differentiation. My basic questions are, should I not expect AUC to lie between .5 and 1 and, which model fit measurement is most appropriate for comparing acros...

Dear Researches, I am using RF (in regression way) for analize several metrics extract from image. I am tuning RF setting a loop using different range of mtry, tree and nodesize using the lower value of MSE-OOB mtry from 1 to 5 nodesize from1 to 10 tree from 1 to 500 using this paper as refery Palmer, D. S., O'Boyle, N. M., Glen, R. C., & Mitchell, J. B. O. (2007). Random Forest Models To Predict Aqueous Solubility. Journal of Chemical Information and Modeling, 47, 150-158. my problem is t...