similar to: SVD Memory Issue

I am using 'tm' package for text mining and facing an issue with finding the frequently occuring terms. From the definition it appears that findFreqTerms and minDocFreq are equivalent commands and both tries to identify the documents with terms appearing more than a specified threshold. However, I am getting drastically different results with both. I have given the results from both the

Buenas tardes grupo. Saludos cordiales Carlos J., muchas gracias por tu orientación. Efectivamente, me había dado cuenta que la razón por la que no se aplicaba colnames era porque no tenía columnas. La cuestión es que no logro visualizar completamente/claramente en qué parte del proceso de creación del corpus se puede hacer. Sin embargo, siguiendo el ejemplo de

Hello, I downloaded LLVM 2.6 and was attempting to compile it with TDM-GCC 4.4.1-tdm2-sjlj + cmake 2.6.4 and this happened: =============Console=================== C:\projects\game-editor\LLVM\build-root>mingw32-make [ 2%] Built target LLVMSystem [ 5%] Built target LLVMSupport [ 7%] Built target tblgen [ 7%] Built target intrinsics_gen [ 10%] Built target LLVMCore [ 12%] Built target

I try to fit a LDA model to a TermDocumentMatrix with the topicmodels package... but R says: > Error in LDA(TDM, k = k, method = "Gibbs", control = list(seed = SEED, : > x is of class ?TermDocumentMatrix??simple_triplet_matrix? > class(TDM) > [1] "TermDocumentMatrix" "simple_triplet_matrix" I try to use a matrix... but don't work: > MAT

Buenas noches grupo. Saludos cordiales. He seguido en la búsqueda de una forma que me permita realizar la comparación de dos documentos pertenecientes a los años 2005 y 2013, y que pueda representar finalmente con wordcloud y con una table en la que las columnas sean los años de cada informe "2005" y "2013", y las filas sean las palabras con la frecuencia de cada una de ellas

Hola, La referencia (gracias por proporcionarla) que has incluido es bastante clara y se puede seguir. ¿Has podido sobre tus dos discursos utilizar la misma lógica? La forma de salir de dudas, para empezar, es que adjuntaras el código que estás empleando por ver si hay algún error evidente. Aunque la forma adecuada para que te podamos ayudar es con un ejemplo reproducible: código + datos.

Buenas tardes, Estoy haciendo un análisis de contenido con el paquete tm. A la hora de ejecutar este código: tdm<-TermDocumentMatrix(corpus,control=list(weighting =weightTf)) tdm.reviews.m<-as.matrix(tdm) La primera línea sí me la ejecuta bien pero en la segunda tengo este error: Error: cannot allocate vector of size 14.0 Gb ¿Cómo puedo corregirlo? Estoy usando la versión de 64bits de

Buenas, El archivo de R ocupa 33 megas. La matriz que quiero construir cupa 14 gb. En el disco local (C) tengo 400 gb disponibles de 670. No estoy muy puesta en trabajar con este tipo de datos. ¿Qué diferencia es trabajar con data.frame? Gracias! El Vie, 7 de Febrero de 2020, 18:07, Xavier-Andoni Tibau Alberdi escribió: > Depende de la operació que quieras hacer con la matriz. Si quitas filas

Muchas gracias Xabier. He intentaddo trabajar con la sparse matrix pero al pasar tdm a matriz me dice también que "cannot allocate a vector of size 12 gb". He hecho tdm<-as.matrix(tdm) ¿Está bien hecho eso para trabajar con la sparse matrix? Gracias! El Lun, 10 de Febrero de 2020, 16:15, Xavier-Andoni Tibau Alberdi escribió: > La respuesta de Carlos creo que es mucho mas

Es la primera vez que trabajo con este tipo de datos...No se si se puede dividir esa matriz. ¿Cómo lo podría hacer? Muchas gracias! El Vie, 7 de Febrero de 2020, 17:55, Xavier-Andoni Tibau Alberdi escribió: > Significa que tus datos són muy grandes y no se pueden guardar en la RAM. > Tienes alternativas para dividir la matriz? > > El vie., 7 feb. 2020 17:26, <miriam.alzate en

Hi Y'all, I am using the text mining package (tm). I am trying to filter out all of the words in a Term Document Matrix that are not in a list of words that I am interested in. I am using the following code: z<-tm_intersect(txt.dtm, c("communications", "safety", "climate", "blood", "surface", "cleanliness",

It is hard to tell from the information that you have provided. Do you have a list of the sizes of all the objects that you have in memory? Are you releasing large objects at the end of each simulation run? Are you using 'gc' to garbage collect any memory after deallocating objects? Collect some additional information with a simple function like below: f_mem_stats <-

Dear R Forum, I have about 2000+ FX forward transactions and I am trying to run 1000 simulations. If I use less no of simulations, I am able to get the desired results. However, when I try to use more than 1000 simulations, I get following error. > sorted2 <- ddply(sorted, .(currency_from_exch, id), mutate, change_in_mtm_bc = mtm_bc - mtm_bc[1]) Error: cannot allocate vector of size 15.6

Dear Sir, Thanks for the guidance. Will check. And yes, at the end of each simulation, a large result is getting stored.? Regards Amelia On Wednesday, 6 April 2016 5:48 PM, jim holtman <jholtman at gmail.com> wrote: It is hard to tell from the information that you have provided.? Do you have a list of the sizes of all the objects that you have in memory?? Are you releasing large

As Jim has indicated, memory usage problems can require very specific diagnostics and code changes, so generic help is tough to give. However, in most cases I have found the dplyr package to be more memory efficient than plyr, so you could consider that. Also, you can be explicit about only saving the minimum results you want to keep rather than making a list of complete results and extracting

Dear R users, I am trying to convert a dataset from one format to several rectangular datasets. A consultant helped design the data entry program for our survey using Delphi/Pascal and for each household the information is stored in a file called "EA-HM-HH.TXT" where EA is the enumeration area number, HM is the homestead number and HH is the household number. Within this file the

I have recently started using "tm" package by Feinerer, K. Hornik, and D. Meyer. While trying to create a term-document matrix from a corpus (approxly 440 docs) I get the following error: tdm <- TermDocumentMatrix(tmp, control=list(weighting=weightTfIdf, minDocFreq=2, minWordLength=3)) *Error in rowSums(m > 0) : 'x' must be an array of at least two dimensions* This error

Hi there, I'm tring a basic asterisk settings. I have a asterisk 1.2.7.1 running on a I have a net with two computers and a router. The router IP in the local net is 192.168.1.1, The first pc has IP: 192.168.1.3 name datile3 . SO GNU Linux. the second pc has IP: 192.168.1.4 name fissun . SO GNU Linux. On datile3, it runs a softphone kphone. From this I want to call the external world. on

Dear helpful person, I have been trying to download package car from the CRAN website using the install.packages command from within R. I have successfully used this command to install other packages but can't make it work for car. When I try I get the following messages: trying URL `http://cran.uk.r-project.org//bin/windows/contrib/PACKAGES' Content type `text/plain' length 5677

https://bugzilla.samba.org/show_bug.cgi?id=6438 Summary: rsync fails to understand IPv6 on Solaris Product: rsync Version: 3.0.6 Platform: x64 URL: http://bink.tajinc.org/tmp2/solaris_rsync_ipv6.patch OS/Version: Solaris Status: NEW Severity: major Priority: P3 Component: core