search for: nclasses

Hello everybody, This is a bug involving functions in core R package: graphics::hist.default, grDevices::nclass.FD, and base::pretty.default. It is not yet on Bugzilla. I cannot submit it myself, as I do not have an account. Could somebody else add it for me, perhaps? That would be much appreciated. Kind regards, Sietse Sietse Brouwer Summary ------- Floating point errors can cause a data

Hi, I am running the following loop, but it takes hours to run as n is big. Is there any way "apply" can be used? Thanks. ### Start nclass <- dim(data)[[2]] - 1 z <- matrix(0, ncol = nclass, nrow = nclass) n <- dim(data)[[1]] x <- c(1:nclass) # loop starts for(loop in 1:n) { r <- data[loop, 1:nclass] classified <- x[r == max(r)]

Hi Louis, You could try this: # find the index of the maximum value in each row of _data_, # disregarding the last column classified <- apply(data[,-(nclass+1)],1,which.max) ## or, if the maximum may be repeated: classified <- apply(data[,-(nclass+1)], 1, FUN = function(x) which(x == max(x))) # the variable _truth_ is just the last column of _data_ ? truth <- data[,nclass + 1] ?table

I just got the same error message with > sessionInfo() R version 3.4.0 (2017-04-21) Platform: x86_64-apple-darwin15.6.0 (64-bit) Running under: macOS Sierra 10.12.4 Matrix products: default BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

Signed-off-by: Marcin Slusarz <marcin.slusarz at gmail.com> --- This patch relies on "drm/nouveau: remove >1 sclass support from nouveau_parent_create_". There are *many* *more* code paths without proper error handling - I counted at least 106 in 41 functions. If someone would like to do a bit of janitorial work I marked those code paths and uploaded "patch" here:

Dear list, I get the following message while computing truehist in R 1.4.1 on Redhat Linux 7.1: > truehist(lsk$Pox, nbins = "FD" , prob = TRUE, xlab = "Pox [mmol/kg]") Error in switch(casefold(nbins), scott = nclass.scott(data), "freedman-diaconis" = , : couldn't find function "nclass.fd" Maybe the "nclass.fd" should be

It's unused (only one codepath passes sclass at all and it's always one), broken (overwrites the same field, leaking previous one) and confusing. Signed-off-by: Marcin Slusarz <marcin.slusarz at gmail.com> --- drivers/gpu/drm/nouveau/core/core/client.c | 2 +- drivers/gpu/drm/nouveau/core/core/parent.c | 3 +--

Is color specification like this available in R for setting postscript colors? > hue <- c(0, seq(from = 0, by = 1/(nclass), length = nclass)) > sat <- c(0, rep(1.0, nclass)) > bri <- c(0, rep(1.0, nclass)) > zcolors <- cbind(hue, sat, bri) > ps.options (setcolor=ps.setcolor.hsb,colors=zcolors)

Please can someone explain to me how to use randomLCA in R for an analysis. I tried using it and had this error (copied below) which indicated my patterns must consist of 0 or 1. I assume I am doing something wrong. Please help. > library(lattice) > library(boot) Attaching package: ‘boot’ The following object(s) are masked from ‘package:lattice’: melanoma > library(utils) >

Hi folks, I know, this is a fairly common question and I am really disappointed that I could not find a solution. I am trying to calculate Mahanalobis distances in a data frame, where I have several hundreds groups and several hundreds of variables. Whatever I do, however I subset it I get the "system is computationally singular: reciprocal condition number" error. I know what it means

Hi I have recently been analyzing birthweight data from a clinic. The data has obvious defects in that there is digit preference on certain weights making them overrepresented. This shows as spikes in the histogram on certain well rounded weights like 2, 2.5, 3, etc. I would like to show this to government officials but can't figure out how I should present the finding in an easy to

...et a step further. My question, perhaps a bit clearer, is how to display the case control status (or any other arbitrary point label) after clustering in a plot: With a bit of pseudo code, where dataset is a data.frame, parameters are those column names where we find numerical values (no NAs) and nclasses is the desired number of classes. fit <- kmeans(dataset[, parameters], nclasses) plot(dataset[, parameters], col = fit$cluster, dimen = nclasses) This gives us a nicely coloured plot where all points are circled. Yet, my desire is to see the case / control-Status encoded in a column "Stat...

Hi Folks, I'd like to know how hist() decides how many cells to use when it ignores my "suggestion" to use say 'hist(...,breaks=50)'. More specifically, I have the results of 10000 simulations, each returning an 8-vector, therefore 8 variables each with 10000 values. Some of these 8 have somewhat skew distributions. Say one of these 8 variables is X. I ask for H <-

Dear list members, I am trying to use the maptools library to display geographical data. At the moment I have some trouble understanding how the " auxvar " variable is supposed to be used in the plot.Map function. I am using R Version 1.8.1 (2003-11-21) on Linux Looking at the plot.Map function itself, I see that it calls a color.ramp function (I am reporting only the relevant

Hi All, I would like to make an invitation to make a collective package with all functions related to TABLES. I know that there are many packages with these functions, the original idea is collect all this functions and to make a single package, because is arduous for the user know all this functions broadcast in many packages. So, I think that the original packages can continue with its

Dear list, I'm trying to do a set of generic functions do make contingency tables from data.frames. It is just running "nice" (I'm learning R), but I think it can be better. I would like to filter the data.frame, i.e, eliminate all not numeric variables. And I don't know how to make it: please, help me. Below one of the my functions ('er' is a mention to EasieR,

Hello: I am using rpart and would like more background on how the splits are made and how to interpret results - also how to properly use text(.rpart). I have looked through Venables and Ripley and through the rpart help and still have some questions. If there is a source (say, Breiman et al) on decision trees that would clear this all up, please let me know. The questions below pertain to a

Hi, is it correct that i need ~ 2GB RAM that it's possible to work with the default setting ntree=500 and a data.frame with 100.000 rows and max. 10 columns for training and testing? P.S. It's possible calculate approximate the memory demand for different settings with RF? Many thanks & regards, Christian

Hi, Is this a bug in truehist()? > library(MASS) > x <- rep(1, 10) > truehist(x) Error in pretty(data, nbins) : invalid 'n' value Thanks, Gad > R.version platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 4.1 year 2006 month 12 day 18 svn

Hi, Is this a bug in truehist()? > library(MASS) > x <- rep(1, 10) > truehist(x) Error in pretty(data, nbins) : invalid 'n' value Thanks, Gad > R.version platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 4.1 year 2006 month 12 day 18 svn