search for: mfinal

Hello, does any one know how to interpret this output in R? > Classification with logitboost > fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20) > summarize(fit, ytest) Minimal mcr: 0 achieved after 6 boosting step(s) Fixed mcr: 0 achieved after 20 boosting step(s) What is "mcr" mean? Thanks [[alternative HTML version deleted]]

...new year. I have got the following error rror in if (nrow(object$splits) > 0) { : argument is of length zero when I am running the following codes. train <- c(sample(1:27,18), sample(28:54, 18), sample(55:81, 8)) a2011.adaboost <- boosting(median_kod ~ ., data = b[train, ], boos=TRUE, mfinal = 10, control = rpart.control(minsplit = 0)) Regards, Greg [[alternative HTML version deleted]]

Hello, I performed a boosting analisis with adabag package to obtain a classification tree with the following set of commands: Tesis.boost <- adaboost.M1(Captura~., data=Tesis2, mfinal=2) > arb<-Tesis.boost$tree[[1]] > post(arb, file ="") > post(arb, file ="",title= "Arbol 1") I would like to know the meanning of the numbers that appeared in the nodes of the tree (in circles and squares)?? For example: 8/120/31 Thanks, BSc. Cecili...

...educed model. After getting the "optimal" random effects structure, I move on and perform a similar procedure on the fixed effects. First of all, does this sound at all sensible? Secondly, when I do this with my data the resulting "optimal" or best fitting model looks like this: mFinal <- lmer( Y ~ aS + bS + c + (d|SpeciesId) + (e|SpeciesId)) d and e show up as random slopes but not in the fixed effects.Is this ok, and if so, I'm not sure what the interpretation is... Thanks so much, HamishUCSD EBEhamishv8@hotmail.com ________________________________________...