similar to: Document classes with tm

I''m looking to use an external node classifier (ENC) in our environment. What''s the easiest way to programmatically get currently applied classes (and class parameters) for all hosts, with the goal of dumping it into a database for later retrieval by the ENC script? Nodes are currently classified via site.pp. thanks -- You received this message because you are subscribed

All, I am sure this is just something I am doing wrong, but I am trying to implement a node classifier (shell script) to have my nodes inherit the proper classes. However, when I run it I am not getting any classes except those that are defined in default. Rather than going into detail showing all of my configurations right off the bat, I have a question: I just stood up a

Hi all, I wonder if there's any way to reshuffle the text collection by the document meta values. For instance, if I have 5 documents that correspond to the following meta data: MetaID Sex Age 0 M 38 0 M 46 0 F 24 0 F 49 0 F 33 Can I reorder the text documents based on the ascending order of age? Thank you very much!! -- View

Hello, I'm trying to using ksvm() in the kernlab package to fit a one-class SVC, but I get a strage result on the cross-validation error estimate. For example, consider this code: data(spam) classifier <- ksvm(type~.,data=spam[which(spam[,'type']=='spam'),], type="one-svc",kernel="rbfdot",kpar=list(sigma=0.1),nu=0.05,cross=10) what I get is: >

Hi, I'm doing a textual analysis of several articles discussing the evolution of prices in order to give a forecast. if someone can give me a clear approach to this knowing that I work on the package tm. Thank you very much -- View this message in context: http://r.789695.n4.nabble.com/any-documents-tp3584961p3584961.html Sent from the R help mailing list archive at Nabble.com.

Le jeudi 09 f?vrier 2012 ? 15:31 +0200, Kari Ruohonen a ?crit : > Hi, > I am trying to replicate a training of AttributeSelectedClassifier with > CFsSubsetEval, BestFirst and NaiveBayes that I have initially done with > Weka. Now, I am trying to use RWeka in R. > > I have a problem of passing arguments to the CfsSubsetEval, BestFirst > and NaiveBayes. I have first created an

Hi, Does it make sense to test a worker class by calling Middleman.new_worker? Or should I just be testing the functionality in the do_work method, with, say, a mock object. This seems like a really ugly DRY violation: you''d need to keep the code in the mock and the real worker in sync. That''s the philosophical half of my question. In fact, until someone tells me why I

I used to use the Web Site Search quite a bit, but it has been down for a couple of weeks. The error that I get is: [general search from the nav bar at top] Not Found The requested URL /search/smb-search.shtml was not found on this server. [search of mail archives] Not Found The requested URL /search/smb-mail.shtml was not found on this server. I've tried a couple of the mirrors but

Hi, I am using some classifiers in RWeka packages and met a couple problems. (1) J48 implements C45 classifier, the C45 should be able to handle missing values in both training set and test set. But I found the J48 classifier can not be evaluated on test set with missing values--it just ignore them. (2) The ensemble classifiers in RWeka such as bagging and boosting: there is a

Dear All, I'm currently doing a project about unsupervised learning, and I'll be using R to analyse a few network traffic datasets downloaded off Andrew Moore's website (http://www.cl.cam.ac.uk/Research/SRG/netos/nprobe/data/papers/sigmetrics/index.html). Could anyone shed some light on how to build a classifier from the training set A, and then use a validation set B to assess the

On Fri, 21 Mar 2003, Remco B. Brink wrote: > Ofcourse to get published in any directory, you need to *specify* that > in the icecast.xml file ;-) the icecast side of it is fine. It *was* working. Then I updated ices2 (the one that worked was October vintage) and now it doesn't work anymore. I suspect that the fascility has been added to ices to specify whether streams are to be

Hi, I am using some classifiers in RWeka packages and met a couple problems. (1) J48 implements C45 classifier, the C45 should be able to handle missing values in both training set and test set. But I found the J48 classifier can not be evaluated on test set with missing values--it just ignore them. (2) The ensemble classifiers in RWeka such as bagging and boosting: there is a

Hola a todos! Tengo algunos problemas con el tamaño de la matriz de términos que obtengo. Los comandos que utilizo son los siguientes: # carga librerias library(tm) library(wordcloud) library(Rstem) library(Snowball) # lee el documento UTF-8 y lo convierte a ASCII txt <-

There's an API elaborated in detail in the doxygen stuff at http:// llvm.org/doxygen/ There's an LLVM Language Reference Manual at http://llvm.org/docs/ LangRef.html, which describes a textual language and its semantics. The preferred mode of operation seems to be to use the API to construct an LLVM tree, and then compile to machine code from the tree. The textual form described in the

Hi, Apology for this question being off the topic (OT) of R, though I expect this list might be the best place on the net to ask this question. In brief, the question is: what classification algorithm can one use if the features are histograms? I have a classification problem, and believe that histograms of the distribution of some values may be the best "feature" to use. To

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

Full_Name: Cesar Telmo Costa Version: R version 2.9.2 (2009-08-24) OS: Ubuntu kermic Submission from: (NULL) (85.241.174.237) AFTER install.packages("tm"): downloaded 317 Kb * Installing *source* package ?tm? ... ** libs gcc -std=gnu99 -I/usr/share/R/include -fpic -g -O2 -c lazyTmMap.c -o lazyTmMap.o gcc -std=gnu99 -shared -o tm.so lazyTmMap.o -L/usr/lib/R/lib -lR ** R ** data

Hi all, I made some computations with the knn function from the class library. If I execute this function several times (with the same parameters k, training set and test set), I obtain different results. I don't understand why the results for my test set are different. Could you give me some explanations? Is the solution for a k-nearest-neighbor classifier unique? Best regards.

> > So i guess from your prev. email the svmModel$coefs correspond to the > "Alpha" . yes (times the sign of y!). > > Why do I see three columns in the coefs?( Is this the number of classes -1 > = Numbe of hyperplanes) yes, but in a packed format which is not trivial. I attach some explanation I sent to R-help some time ago (the guy wanted to write his own

I have R installed on my computer and want to use the tm module. I selected a CRAN mirror then selected tm on the install package menu. This is the response I got: also installing the dependency ?slam? trying URL 'http://cran.mirrors.hoobly.com/bin/windows/contrib/2.11/slam_0.1-13.zip' Content type 'application/zip' length 41992 bytes (41 Kb) opened URL downloaded 41 Kb trying