similar to: Discriminant analysis - stepwise procedure

Hi, Jiong, Thanks for the patch! It is a great start to support 32bit register in BPF. In the past, I have studied a little bit to see whether 32bit register support may reduce the number of unnecessary shifts on x86_64 and improve the performance. Looking through a few bpf programs and it looks like the opportunity is not great, but still nice to have if we have this capability. As you

All, If we can speculatively execute a load instruction, why isn’t it safe to hoist it out by promoting it to a scalar in LICM pass? There is a comment in LICM pass that if a load/store is conditional then it is not safe because it would break the LLVM concurrency model (See commit 73bfa4a). It has an IR test for checking this in test/Transforms/LICM/scalar-promote-memmodel.ll However, I have

Hi, a colleague ran a stepwise discriminant analysis twice in a row and got different results, suggesting some "sochasticity" in the algorithms involved. I looked at her data and found that there was a lot of collinearity, so that I reckoned that maybe "stepclass" (klaR) cannot find a clear winner when trying to include a new variable and makes a random choice. Is that true?

I think gcc is right. It inserted a branch for n == 0 (the cbz at the top), so that's not a problem. In all other regards, this is safe: if you examine the sequence of loads and stores, it eliminated all but the first load and all but the last store. How's that unsafe? If I had to guess, the bug here is that LLVM doesn't want to hoist the load over the condition (which it is right

Thanks for the background on the concurrent memory model. So, is it sufficient that the loop entry is guarded by condition (cbz at top) for preventing the race? The loop entry will be guarded by condition if loop has been rotated by loop rotate pass. Since LICM runs after loop rotate, we can use ScalarEvolution::isLoopEntryGuardedByCond to check if we can speculatively execute load without

Hi, I'm trying to use "stepclass" to do a stepwise variable selection with method=lda. I keep getting this warning message, which shows up once for each variable added to the model during variable selection: Warning message: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, I don't know how to interpret this warning. I

Hi! I got the following runtime error when I tried to use svm method with stepclass. Error in "colnames<-"(`*tmp*`, value = c("0", "1")) : attempt to set colnames on object with less than two dimensions I repeated the same sequence of statements but this time I used the classification function used in the example, i.e., "lda" and it worked fine

I use Windows, R version 2.5.1 When I try to run stepclass (klaR) I get an error message/warning saying: 1: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, ... Actually, I look 16 warnings of this type. Can anyone tell me what this means? Also, it returns only 2 out of the 79 variables as important, however these variables

Airon, I don't think you have to find an English computer 'cause the following must work in your Chinese one :-) Let me explain. First of all, change your lines to xdata <- ckhdat$Adj..Close[1:1447] #names(ckhdwt.la8) <- c("w1", "w2", "w3", "w4", "w5","w6", "v6") note the # sign, i.e., DO NOT change the names

Hi All, I've encountered an issue where tail merging MIs is causing a problem with the post-RA MI scheduler dependency analysis and I'm not sure of the best way to address the problem. In my case, the branch folding pass (lib/CodeGen/BranchFolding.cpp) is merging common code from BB#14 and BB#15 into BB#16. It's clear that there are 4 common instructions (marked with an *) in BB#14

Dear all, I need to compute the ACF (autocorrel) of an AR6 process, given the values of its parameters (w1,w2,w3,w4,w5,w6). First, I notice that there is an error as soon as the sum of the wi equals 1 : "Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number = 1.00757e-18"

Hello R list, I'm looking to do some stepwise discriminant function analysis (DFA) based on the minimization of Wilks' lambda in R to end up with a composite signature (of metals "Al","Sb","Bi","Cr","Ba") capable of discriminating 100% of the source factors (LANDUSE: "A","B","C"). The Wilks' lambda

Hi all, is it possible to do stepwise discriminant analysis (linear amnd non-linear) in R? If yes- which package does it|? Thanks Janine -------------------------------------------- "El gesto y la palabra son el pensamiento del hombre" Isabel Allende Janine Illian lecturer in statistics SIMBIOS School of Computing University of Abertay Dundee Bell Street Dundee, DD1 1HG Scotland,

I don't understand which is the problem Could you help me please? Thanks in advance Marta > str(data_indiciN2) 'data.frame': 200 obs. of 36 variables: $ gruppo: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ... $ I001N2: num 19.32 8.22 28.35 7.24 14.7 ... $ I002N2: num 2.92 2.54 0.11 1.6 7.12 ... $ I003N2: num -22.362 -0.222 -19.291

Hi Oliver, Thanks for trying this. Could you file a different PR for each of the problem you found and reference the umbrella PR: http://llvm.org/PR35347? <http://llvm.org/PR35347?> Thanks, -Quentin > On Nov 17, 2017, at 8:17 AM, Oliver Stannard <oliver.stannard at arm.com> wrote: > > Hi Quentin, > > One more reproducer, this time with small (<64bit) values

Dear All, I am looking at discriminating among several individuals based on a few variable sets (I think some variables do not make sense unless they are entered together, so I "force" them into the models together, hence datasets). I have done so with linear discriminant analysis (LDA) using "MASS::lda", with acceptable results. However, one of my collaborators

AArch64AddressTypePromotion.cpp does a fair bit of work to help make these things work out well. It could probably be generalized for non-AArch64 targets as per the comment in the file header. > On Jun 26, 2014, at 10:42 AM, Sanjay Patel <spatel at rotateright.com> wrote: > > Cool HW trick. :) > Are those 'sxtw' ops free? > That’ll depend on the details of the

--l4Siqd0eqV Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: 7bit Hello, I run the following job. Please, compare the results of summary and table concerning berufl. From similar SPSS/PSPP runs, the result of table is correct. Did I misunderstand anything or is there a bug? What does the difference come from? What does '(other)' mean? What about the strange

Thanks all. Amara, could you take a look? > On Nov 20, 2017, at 3:06 AM, Oliver Stannard <oliver.stannard at arm.com> wrote: > > Hi Quentin, > > I’ve raised: > https://bugs.llvm.org/show_bug.cgi?id=35359 <https://bugs.llvm.org/show_bug.cgi?id=35359> > https://bugs.llvm.org/show_bug.cgi?id=35360 <https://bugs.llvm.org/show_bug.cgi?id=35360> >

any news? ---------- Forwarded message ---------- From: Emin Hasanov <emin@hasanov.com> Date: May 10, 2006 11:50 AM Subject: Fwd: ?????????? To: Rovshan Baghirov <rovshanb@gmail.com> Rovshan, how would you estimate this work in terms of manhours? ---------- Forwarded message ---------- From: Anar Ibrahimov < anar@autostar.az> Date: May 10, 2006 11:22 AM Subject: ??????????