similar to: boosting for multi-class classification

Are there any packages to handle multi-class classification with boosting. I know adaboost function include in package "boost" but that is only for two-class. Thanks for your help. Xiyan Lon

Hi List, Is it possible to define how 'in' works for an object of a specific class (to achieve a similar result to implementing the iterator protocol in a class Python)? Cheers, Simon Knapp [[alternative HTML version deleted]]

Hi all, Could you please give me some pointers about what's the best boosting package in R currently? in terms of classification accuracy? And any pointers about tutorials and study-materials to curb the learning curve will be greatly appreciated! Thank you! p.s. Does anybody happen to know Boosting implemented in other language such as Matlab? Are they good in terms of accuracy? What

Hi I am using boosting for a classification and prediction problem. For some reason it is giving me an outcome that doesn't fall between 0 and 1 for the predictions. I have tried type="response" but it made no difference. Can anyone see what I am doing wrong? Screen output shown below: > boost.model <- gbm(as.factor(train$simNuance) ~ ., # formula +

I don't understand why I get the following results. I define two classes 'Base' and 'Derived', the latter of which 'contains' the first. I then define a generic method 'test' and overload it for each of these classes. I call 'callNextMethod()' in the overload for Derived. From the output, it appears that the overload for Base gets called twice. Why is

Hi R Helpers, I am a long time RWinEdt user and have just acquired a new laptop. I have installed RWinEdt and things are going smoothly except for one small glitch - file names are not appearing on the document tabs. When I use WinEdt (as opposed to RWinEdt), they are appearing. Can anyone offer any advice on this? Thanks in advance, Simon Knapp OS: windows7 Arch: 64 bit R version: 2.13.0

Hello everyone, I want to get a 1km by lkm grid raster image using my csv data. If I call latitude=a, longitude=b and preciptation=c. a<-(1,2,3,4,5) b<-(6,7,8,9,10) c<-(10,20, 30,40, 50) Then I found an example in r help which goes like pts = read.table("file.csv",......) library(sp) library(rgdal) proj4string(pts)=CRS("+init=epsg:4326") # set it to lat-long pts =

I'm interested in further understanding the differences in using many classification trees to improve classification rates. I'm also interested in finding out what I can do in R and which methods will allow prediction. Can anybody point me to a citation or discussion? Specifically, I want to classify remotely sensed imagery where training data is extracted on class membership by the user.

Dear R users, I’m trying to understand how correlated predictors impact the Relative Importance measure in Stochastic Boosting Trees (J. Friedman). As Friedman described “ …with single decision trees (referring to Brieman’s CART algorithm), the relative importance measure is augmented by a strategy involving surrogate splits intended to uncover the masking of influential variables by others

Hi List, I am building a package for a client to help them create and perform analyses against netcdf files which contain 'a temporal stack' of grids. For my examples and test cases, I create an example dataset in code (as this is a lot more space efficient than providing raw data). The code creates a netcdf file in tempdir() and an object of class 'ncdf' in the global namespace.

Background: I have an algorithm which produces a large number of small polygons (of the spatial kind) which I would like to use within R using objects from sp. I can't predict the exact number of polygons a-priori, the polygons will be grouped into regions, and each region will be filled sequentially, so an appropriate C++ 'framework' (for the point of illustration) might be: typedef

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]]

Hi, I am trying to implement the Adaboost.M1. algorithm as described in "The Elements of Statistical Learning" p.301 I don't use Dtettling 's library "boost" because : - I don't understande the difference beetween Logitboost and L2boost - I 'd like to use larger trees than stumps. By using option weights set to (1/n, 1/n, ..., 1/n) in rpart or tree

Dear R-users, I have a set of 12000 image samples. I can divide this set into two categories: training and testing. I need to classify the test set into a two qualitative outputs: true or false for some characteristic. To do the classification I'm using the packages SVM in e1071 library and LDA in the MASS library. However, I'm with a great number of FALSE POSITIVE CASES in both

Hi, Dear R community, Does anyone know how to constructdecision tree with boosting? Is any tutorial I can read? -- Sincerely, Changbin -- [[alternative HTML version deleted]]

Hai all, We are working on Multi-class Classification. Currently up to 1.1 million records Ranger package in R is able to handle. Training time on 128 GB RAM is 12 days, which is not a practically feasible method to proceed further. In future we will have dataset of dimension 10 million records, we are in search for a package or framework which can handle 10 million records with at least 12000

Hi UseRs - I am new to R, and could use some help making out-of-sample predictions using a boosting model (the mboost command). The issue is complicated by the fact that I have panel data (time by country), and am estimating the model separately for each country. FYI, this is monthly data and I have 1986m1 - 2009m12 for 9 countries. To give you a flavor of what I am doing, here is a simple

Hi Karol, I have some comments below. On 05:42 PM - Dec 01 2015, Karol Herbst wrote: > 0: disable boosting (cap to base clock from the vbios) > 1: boost only to boost clock from the vbios > 2: boost to max clock available > --- > drm/nouveau/include/nvkm/subdev/clk.h | 10 +++++++++- > drm/nouveau/nvkm/subdev/clk/base.c | 17 ++++++++++++++++- >

There was errors when I tried to start the script recommended by Andrew to boost bandwidth for voip http://www.mixdown.ca/~andrew/dump/rc.tc. This is the output I get : ./rc.tc start RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File exists RTNETLINK answers: File

Webinar signup: Advances in Gradient Boosting: the Power of Post-Processing December 14, 10-11 a.m., PST Webinar Registration: http://2.salford-systems.com/gradientboosting-and-post-processing/ Course Outline: * Gradient Boosting and Post-Processing: o What is missing from Gradient Boosting? o Why post-processing techniques are used? * Applications Benefiting from