search for: truthfully

Trying to resolve some general tablegen questions. Consider the test case for Tablegen called eq.td class Base<int V> { int Value = V; } class Derived<string Truth> : Base<!if(!eq(Truth, "true"), 1, 0)>; def TRUE : Derived<"true">; def FALSE : Derived<"false">; If I process this through tablegen I get: ------------- Classes

>From my understanding, NAME is a special builtin entry and dedicated for things related multiclass, So, is the following rewrite what you want? class Base<int V> { int Value = V; } class Derived<string Truth> : Base<!if(!eq(Truth, "true"), 1, 0)>; multiclass Derived_m<string T> { def #NAME# : Derived<T>; } defm TRUE :

I have access to a cluster on which I have been supplied with R 3.1.0 which appears to have been built using the intel compiler tools. The following minimal Fortran file: subroutine truth(lind) logical lind lind = .TRUE. end Compiles thusly: arcadia> R CMD SHLIB truth.f ifort -fpic -O3 -xHOST -axCORE-AVX-I -fp-model precise -c truth.f -o truth.o ifort: command

I hope this question is adequate for this list I use the nnet code from V&R p. 348: The very nice and general function CVnn2() to choose the number of hidden units and the amount of weight decay by an inner cross-validation- with a slight modification to use it for classification (see below). My data has 2 classes with unequal size: 45 observations for classI and 116 obs. for classII With

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

Has anyone seen this: http://www.microsoft.com/windows/Embedded/sak/evaluation/compare/advantage.asp And has anyone from the Samba team posted a response? It seems like some of the information presented there is contrary to what I know about Samba. ERX

According to the TableGen manual: "Each def record has a special entry called "NAME." This is the name of the def ("ADD32rr" above). In the general case def names can be formed from various kinds of string processing expressions and NAME resolves to the final value obtained after resolving all of those expressions. The user may refer to NAME anywhere she desires to

Hi All, I am trying to use a neural network for my work, but I am not sure about my approach to select a parsimonious model. In R with nnet, the IAC has not been defined for a feed-forward neural network with a single hidden layer. Is this because it does not make sens mathematically in this case? For example, is this pseudo code sensible? Thanks in advance for your help. I am sorry if this

According to the documentation at http://docs.puppetlabs.com/puppet/2.7/reference/lang_conditional.html#if-statements, you can test for truth with syntax like this: if $is_virtual == ''true'' { AFAICT that''s not the case. The quotes around ''true'' make the comparison always fail. Here''s my test case class users {

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)]

Dear R-users, dear Prof. Ripley as package maintainer I tried to investigate the odd error, when I call nnet together with a 'weights' parameter, using the 'fgl' example in V&R p 348 The error I get is: Error in eval(expr, envir, enclos) : Object "w" not found I think it is a kind of scoping problem, but I really cannot see, what the problem exactly is. and

Dear R-users I use nnet for a classification (2 classes) problem. I use the code CVnn1, CVnn2 as described in V&R. The thing I changed to the code is: I define the (class) weight for each observation in each cv 'bag' and give the vector of weights as parameter of nnet(..weights = weight.vector...) Unfortunately I get an error during some (but not all!) inner-fold cv runs:

This was intended to go to the mailing list :) -------------- next part -------------- An embedded message was scrubbed... From: Maik Merten <maikmerten@gmx.net> Subject: Re: [Theora] troll or truth ? Date: Wed, 23 Mar 2005 01:40:00 +0100 Size: 1111 Url: http://lists.xiph.org/pipermail/theora/attachments/20050323/5fe9d818/Theoratrollortruth-0001.mht

Does Puppet have any genuine concept of truth and nil that survives the interface with Ruby? has_variable? only returns false if a variable has never been assigned a value at all in the enclosing scope; there is no way to assign undef to a regular variable (as opposed to a resource parameter) within a scope and so make it undefined for the template. It would be a very useful thing to be able to

I made one typo in my previous mail.   May I ask one statistics related question please? I have one query on MLE itself. It's property says that, for large sample size it is normally distributed [i.e. asymptotically normal]. On the other hand it is "Consistent" as well. My doubt is, how this two asymptotic properties exist simultaneously? If it is consistent then asymptotically it

On Thu, 2016-04-28 at 18:37 +0300, Michael S. Tsirkin wrote: > OK, so for intel, it seems that it's enough to set > pdev->dev.archdata.iommu = DUMMY_DEVICE_DOMAIN_INFO; > for the device. Yes, currently. Although that's vile. In fact what we *want* to happen is for the intel-iommu code simply to decline to provide DMA ops for this device, and let it fall back to the swiotlb or

On Thu, 2016-04-28 at 18:37 +0300, Michael S. Tsirkin wrote: > OK, so for intel, it seems that it's enough to set > pdev->dev.archdata.iommu = DUMMY_DEVICE_DOMAIN_INFO; > for the device. Yes, currently. Although that's vile. In fact what we *want* to happen is for the intel-iommu code simply to decline to provide DMA ops for this device, and let it fall back to the swiotlb or

Hi, The signature of mget() changed between R-2.15.1 and recent R-devel. In R-2.15.1: > args(mget) function (x, envir, mode = "any", ifnotfound = list(function(x) stop(paste0("value for '", x, "' not found"), call. = FALSE)), inherits = FALSE) NULL In R-devel: > args(mget) function (x, envir, mode = "any", ifnotfound

Hi I have a scatterplot of points with pch=1 and a single point with pch=3, lwd=3. It has a high line width to attract attention to it. The following script plot(rnorm(10),rnorm(10),col="black") points(rnorm(10),rnorm(10),col="red") points(0,0,pch=3,lwd=3) if(TRUE){ legend("bottomleft",c("a","b","Truth"),pch=c(1,1,3),col=c

Dear list, I think I'm being dense, but I can't get combn or expand.grid to give me this result. I need to generate a matrix of all 16 possible sequences of 4 boolean elements, 0000 0001 0010 0011 0100 ..... 1111 (in the end I'll have to assign NA to the 0s and some value to the 1s but let's keep it simple) OK, I could go the following route, but I feel like reinventing the