search for: eev

Hello, I am using the parameterized EM- Algorithm in clustering context. I use generated datasets, containing 5000 points in 20 dimensions with 5 clusters. The following poses a problem for me: emEst<-me(modelName="EEV",data=data[,1:numDimensions],z=unmap(x)) emEst<-me(modelName="VEV",data=data[,1:numDimensions],z=unmap(x)) coordProj(main="Model EEV",data,dimens=c(1,2),type="classification",ask=F,mu=emEst$mu,sigma=em Est$sigma,z=emEst$z) coordProj(main=&q...

...e error rate equals 18%, so k-means (EII) is worse then VVV, what is clear for me. I would like to apply model-based to economic data set (GDP, life expectancy data of UE countries), because I am PhD student of University of Economics in Poland. Using this data (standardized) I get the best model EEV (2 classes), EII (k-means) curve is under EEV curve what suggests that k-means is worse then EEV, but class error for EII equals 0 and for EEV= 6% (and more for another variables), why? Even applying iris data we get lower class error for EII model (10%) than for VEV (33%) for 2 classes, in sp...

Hello All... I gave a task to my students that involved using mclust to look for clusters in some bivariate data of isotopes vs various mining locations. They discovered something I didn?t expect; the data (called tur) is appended below. p <- qplot(x = dD, y = dCu65, data = tur, color = mine) print(p) # simple bivariate plot of the data; looks fine mod1 <- Mclust(tur[,2:3]) mod1$G mod2

...o have a look at http://dl.dropbox.com/u/5685598/dataedges.csv ). Now, I would like to use the info on columns 1,2 and 4 to predict the value in column 3. However, when I run the script below (obg_mining_script.R), I get errors and plenty of warnings. source('obg_mining_script.R') EEV EEI EEI EEE EEE EII EII EII EII EII EII EII E 3 4 3 3 2 8 5 8 2 9 2 9 2 [1] "OK training" Error in cdensE(data = data, logarithm = TRUE, parameters = parameters, : data must be one-dimensional In addition: There were 42 warnings (use warnings() to see them...

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