[R] fixed set.seed + kmeans output disagree on distinct platforms
Iago Giné Vázquez
|@go@g|ne @end|ng |rom @jd@e@
Wed Sep 4 07:23:48 CEST 2024
Hi all,
I build a dataset processing in the same way the same data in Windows than in Linux.
The output of Windows processing is: https://gitlab.com/iagogv/repdata/-/raw/main/exdata.csv?ref_type=heads
The output of Linux processing is: https://gitlab.com/iagogv/repdata/-/raw/main/exdata2.csv?ref_type=heads
exdata=as.matrix(read.csv("https://gitlab.com/iagogv/repdata/-/raw/main/exdata.csv?ref_type=heads", header=FALSE))
exdata2=as.matrix(read.csv("https://gitlab.com/iagogv/repdata/-/raw/main/exdata2.csv?ref_type=heads", header=FALSE))
They are not identical (`identical(exdata,exdata2)` is FALSE), but they are essentially equal (`all.equal(exdata,exdata2)` is TRUE). If I run
set.seed(20232260)
exkmns <- kmeans(exdata, centers = 7, iter.max = 2000, nstart = 750)
I get
exkmns$centers
V1 V2 V3 V4 V5 V6
1 -0.4910731 -0.2662055 0.57928758 0.14267293 -0.03013791 0.106472717
2 0.5301237 0.2815620 -0.23898532 1.00979412 -0.26123328 0.068099931
3 0.2255298 -0.5165964 -0.02498471 -0.20438275 -0.41224195 -0.107538855
4 -0.2616257 0.5680582 0.55387437 -0.09562789 -0.01706577 -0.028248679
5 -0.4820078 -0.1667370 -0.46533618 -0.05271446 0.05477352 0.005236259
6 0.6455994 -0.1396674 0.05988547 -0.15557399 0.62766365 0.031051986
7 0.1072127 0.5538876 -0.33117098 -0.43209203 -0.18646403 -0.081273130
both in Windows (1) and in Linux (2, 3) up to rows order. If I run in Linux in my computer (2)
set.seed(20232260)
exkmns2 <- kmeans(exdata2, centers = 7, iter.max = 2000, nstart = 750)
then, I get
exkmns2$centers
V1 V2 V3 V4 V5 V6
1 0.64559941 -0.1396674 0.05988547 -0.15557399 0.62766365 0.03105199
2 -0.26162573 0.5680582 0.55387437 -0.09562789 -0.01706577 -0.02824868
3 0.53012369 0.2815620 -0.23898532 1.00979412 -0.26123328 0.06809993
4 0.03409765 0.3492520 -0.36910409 -0.40721418 -0.21482793 0.03073180
5 -0.58527394 -0.1790337 -0.46778956 0.03573883 0.15473589 -0.07980379
6 -0.49107314 -0.2662055 0.57928758 0.14267293 -0.03013791 0.10647272
7 0.22552984 -0.5165964 -0.02498471 -0.20438275 -0.41224195 -0.10753886
therefore, all rows essentially equal except for rows 5 and 7 of first dataset (5 and 4 of second dataset). With a bit more detail:
*
Row 0.2255298 -0.5165964 -0.02498471 -0.20438275 -0.41224195 -0.107538855 belongs to exdata (and exdata2) and is center of both outputs
*
Row 0.1072127 0.5538876 -0.33117098 -0.43209203 -0.18646403 -0.081273130 belongs to the dataset and it is only center of exdata output
*
Row -0.4820078 -0.1667370 -0.46533618 -0.05271446 0.05477352 0.005236259 does not belong to the dataset and it is only center of exdata output
*
Row -0.58527394 -0.1790337 -0.46778956 0.03573883 0.15473589 -0.07980379 belongs to the dataset and it is only center for exdata2 on Linux in my computer
*
Row 0.03409765 0.3492520 -0.36910409 -0.40721418 -0.21482793 0.03073180 does not belong to the dataset and it is only center for exdata2 on Linux in my computer
*
All other 4 rows (1,2,4 and 6 of first output) do not belong to the dataset and are common centers.
Even, further, if I run
set.seed(20232260)
exkmns <- kmeans(exdata, centers = 7, iter.max = 2000, nstart = 750)
in posit.cloud (3), I get the same result than above. However, if I run (both in posit.cloud or in Windows)
set.seed(20232260)
exkmns2 <- kmeans(exdata2, centers = 7, iter.max = 2000, nstart = 750)
then I get
exkmns2$centers
V1 V2 V3 V4 V5 V6
1 0.6426035 -0.1449498 0.05843435 -0.1527968 0.62943077 0.02984948
2 -0.4092382 -0.3740695 0.69597037 0.1956896 -0.05026200 -0.01453132
3 0.1072127 0.5538876 -0.33117098 -0.4320920 -0.18646403 -0.08127313
4 0.2255298 -0.5165964 -0.02498471 -0.2043827 -0.41224195 -0.10753886
5 0.5301237 0.2815620 -0.23898532 1.0097941 -0.26123328 0.06809993
6 -0.5223387 -0.1484517 -0.38982567 -0.0341488 0.06446446 0.03622056
7 -0.2701703 0.5263218 0.52942311 -0.1112202 -0.03460591 0.03577287
So only its rows 4 and 5 are common centers to both of previous outputs and row 3 is common width exdata centers.
Does all this have any sense?
Thanks!
Iago
(1)
R version 4.4.1 (2024-06-14 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 10 x64 (build 19045)
Matrix products: default
(2)
R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Debian GNU/Linux 12 (bookworm)
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.21.so; LAPACK version 3.11.0
(3)
R version 4.4.1 (2024-06-14)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 20.04.6 LTS
Matrix products: default
BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so; LAPACK version 3.9.0
[[alternative HTML version deleted]]
More information about the R-help
mailing list