search for: bagging

Ok, so I'm slowly figuring out what a factor is, and was able to follow the related thread about finding a mode by using constructs like my_mode = as.numeric(names(table(x))[which.max(table(x))]) Now, suppose I want to keep looking for other modes? For example, Rgames> sample(seq(1,10),50,replace=TRUE)->bag Rgames> bag [1] 2 8 8 10 7 3 2 9 8 3 8 9 6 6 10 10 7 1

Even reading the documentation I can not figure out what is the select_tag difference between this: <% = select_tag (bags [], "options_for_select (bags.collect @ {| bb | [bb.bag_type, bb.id]}, ruser.bags.collect @ {| ub | ub.id}), {: multiple => true,: id => "bags"})%> and this: <% = select_tag "bags [], " options_for_select (bags.collect @ {| bb

I''ve got some of this working but other parts are ellusive. I have CREATE TABLE `bags` ( `id` int(11) NOT NULL auto_increment, `name` varchar(255) NOT NULL default '''', PRIMARY KEY (`id`) CREATE TABLE `packages` ( `id` int(255) NOT NULL auto_increment, `name` varchar(255) NOT NULL default '''', PRIMARY KEY (`id`) CREATE TABLE

All, I am looking at an example in Aliaga's Interactive Statistics. Bag A has the following vouchers. BagA <- c(-1000,10,10,10,10,10,10, 10,20,20,20,20,20,20,30, 30,40,40,50,60) Bag B has the following vouchers. BagB <- c(10,20,30,30,40,40,50,50, 50,50,50,50,60,60,60,60, 60,60,60,1000) Two values are selected (from BagA or BagB) without

Hi, Is here anyone knows the difference between rapart and bagging when grow a CART tree? Thanks Qin

Good morning all. I am doing bagging with package caret. I need bagging for a classification problem. I am working with " bag". bag(x, y, B = 10, vars = NULL, bagControl = bagControl(), ...) bagControl(fit = NULL, predict = NULL, aggregate = NULL, downSample = FALSE) My fit function is:...

Hello, I''m not yet a camping guru nor a RESTafarian, but I try. Currently I''m trying to build a rest-style web app with sleeping bag/camping and I may successfully access the index, show, new, create and edit methods, that are provided with sleeping bag. But I don''t know, how to build a form or link to access destroy and update. I think this is mainly because of the

Hello! Does anyone know how to apply bagging for SVM? ( for example) I am using adabag package to execute bagging but this method, "bagging", works with classification trees. I would like to apply my bagging to other classifiers as SVM,RNA or KNN. Has anyone do it? Thanks!! [[alternative HTML version deleted]]

Dear Sir, I am a R beginning user. I would like to apply the bagging algorithm to my data in order to classify a certain disease by Bagging Support Vector Machine Ensemble. My problem is that even if I am reading the book, looking at the examples in internet and available in R, learning a lot of theoretical things on about SVM esemble or Bagging method, I can't...

Has anyone any experience of applying observational weights in bagging? I am performing regression trees (continuous data on bird abundance) and need to account for sampling intensity. In a single tree, i.e. a call of rpart, I can specify weights either by having a separate vector called weights, or by a variable called weights in the dataframe under analysis. Both pr...

I am using bagging to perform Bagged Regression Trees on count data (bird abundance in Britain and Ireland, in relation to climate and land cover variables). Predictions from the final model are visually believable but I would really like a diagnostic equivalent to classification success that can be used to decide if...

I'm having the most weird problem with bagging function. For some unknown reason it does not improve the classification (compared to rpart), but instead gives much worse results ! Running rpart on my data gives error rate of about 0.3 and bagging, instead of improving this results, gives error rate of 0.9 !!! I'm running both rpart and b...

Hi, Dear Greg, Sorry to bother you again. I have several questions about the 'gbm' package. if the train.fraction is less than 1 (ie. 0.5) , then the* first* 50% will be used to fit the model, the other 50% can be used to estimate the performance. if bag.fraction is 0.5, then gbm use the* random* 50% of the data to fit the model, and the other 50% data is used to estimate the

I''m trying to pull ou the ''name'' field for each of my associated rows and pass it as a string of names. I''m missing something obvious here but I thought @bag.packages.name.join(", ") would work. do I have to loop through @bag.packages? that seems like the long way. thanks -zac -- Posted via http://www.ruby-forum.com/.

Dear all, I have a problem with the function "bagged clustering" of package e1071. When I try to run the example of bagged clustering with the iris data : data(iris) bc1 <- bclust(iris[,1:4], 3, base.centers=5) I got the following message error : Loading required package: class Committee Member: 1(1) 2(1) 3(1) 4(1) 5(1) 6(1) 7(1) 8(1) 9(1) 10(1)Error in bclust(iris[, 1:4], 3,

...ith cross-validation produces two models - one of which predicts gender for Males well, and Females poorly, and the other does the opposite (Females well, and Males poorly). In both cases the error rate for the worse predicted gender is close to 50%, and for the better predicted gender about 15%. Bagging tree models produces a model which classifies both males and females equally well (or equally poorly), but has an overall error rate (just over 30%) higher than either of the rpart models (about 25%). My instinct is to go for the bagging results, as they seem more reasonable, but my colleagues rea...

...following for all different valies of ns: library(rpart) library(ipred) data("Forbes2000", package="HSAUR") Forbes2000 <- subset(Forbes2000, !is.na(profits)) datasize=length(Forbes2000$profits) f <- rpart(profits ~ assets + marketvalue + sales, data=Forbes2000) fb <- bagging(profits ~ assets + marketvalue + sales, data=Forbes2000) fb <- bagging(profits ~ assets + marketvalue + sales, data=Forbes2000, nbagg=100,coob=TRUE) fb <- bagging(profits ~ assets + marketvalue + sales, data=Forbes2000, nbagg=100,coob=TRUE, ns=round(.9*datasize))...

Dear sir, If I want to use bagging with SVM, which package should I choose?Thanks! Best wishes,Jie _________________________________________________________________ [[alternative HTML version deleted]]

Hello all. I am using method "bag()" to develop a bagging with my dataset. When I do bag( dataP, dataP$Score, B=10) I obtain this error: error en bag.default(Score ~ ., data = dataP, B = 10) : entrada en evaluacion: recursivo por defecto o problemas anteriores? ( in english, evaluating input: default recursive or previous problems?) Any idea? Than...

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