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| NOTES: (1) a maintainance reboot of lemming prevented these builds to complete on this machine (2) these are the last builds with R 2.6.0 (2007-06-03 r41797) on lamb1 and lemming, next builds will be with R 2.6.0 (2007-06-10 r41908) configured with --enable-strict-barrier |
| Package 142/238 | Hostname | OS | Arch | BUILD | CHECK | BUILD BIN |
MLInterfaces1.11.2V. CareyLast Changed Date: 2007-05-11 21:56:41 -0700 Last Changed Rev: 24616 | lamb1 | Linux (SUSE 10.1) | x86_64 | OK | ERROR | |
| wellington | Linux (SUSE 9.2) | i686 | OK | ERROR | ||
| churchill | Solaris 2.9 | sparc | OK | ERROR | ||
| lemming | Windows Server 2003 (32-bit) | x64 | OK | [ ERROR ] | skipped |
| Package: MLInterfaces |
| Version: 1.11.2 |
| Command: D:\biocbld\bbs-2.1-bioc\R\bin\R.exe CMD check MLInterfaces_1.11.2.tar.gz |
| RetCode: 1 |
| Time: 190.4 seconds |
| Status: ERROR |
| CheckDir: MLInterfaces.Rcheck |
| Warnings: NA |
* checking for working latex ... OK
* using log directory 'D:/biocbld/bbs-2.1-bioc/meat/MLInterfaces.Rcheck'
* using R version 2.6.0 Under development (unstable) (2007-06-03 r41797)
* checking for file 'MLInterfaces/DESCRIPTION' ... OK
* this is package 'MLInterfaces' version '1.11.2'
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking whether package 'MLInterfaces' can be installed ... OK
* checking package directory ... OK
* checking for portable file names ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking for unstated dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... NOTE
makeCVFunc: multiple local function definitions for 'resfunc' with
different formal arguments
* checking Rd files ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* creating MLInterfaces-Ex.R ... OK
* checking examples ... ERROR
Running examples in 'MLInterfaces-Ex.R' failed.
The error most likely occurred in:
> ### * knnB
>
> flush(stderr()); flush(stdout())
>
> ### Name: knnB
> ### Title: An interface to various machine learning methods for
> ### ExpressionSets
> ### Aliases: allClass stat.diag.daB
> ### stat.diag.daB,ExpressionSet,character,integer-method cvB knn1B knnP
> ### lcaB logitboostB lvq2B lvq3B olvq1B predLabels RObject knnB nnetB
> ### lvq1B naiveBayesB svmB baggingB ipredknnB sldaB ldaB qdaB pamrB
> ### rpartB randomForestB gbmB allClass,classifOutput-method
> ### cvB,ExpressionSet,character-method predLabels,MLOutput-method
> ### predLabels,classifOutput-method last.warning distMat,MLOutput-method
> ### RObject,MLOutput-method trainInds,classifOutput-method
> ### show,probMat-method show,probArray-method show,membMat-method
> ### show,qualScore-method show,silhouetteVec-method show,MLOutput-method
> ### baggingB,ExpressionSet,character,integer-method
> ### gbmB,ExpressionSet,character,integer-method
> ### ipredknnB,ExpressionSet,character,integer-method
> ### knn1B,ExpressionSet,character,integer-method
> ### knnB,ExpressionSet,character,integer-method
> ### lcaB,ExpressionSet,numeric-method
> ### ldaB,ExpressionSet,character,integer-method
> ### logitboostB,ExpressionSet,character,integer,numeric-method
> ### lvq1B,ExpressionSet,character,integer-method
> ### lvq2B,ExpressionSet,character,integer-method
> ### lvq3B,ExpressionSet,character,integer-method
> ### naiveBayesB,ExpressionSet,character,integer-method
> ### nnetB,ExpressionSet,character,integer-method
> ### olvq1B,ExpressionSet,character,integer-method
> ### pamrB,ExpressionSet,character,integer-method
> ### qdaB,ExpressionSet,character,integer-method
> ### randomForestB,ExpressionSet,character,integer-method
> ### rpartB,ExpressionSet,character,integer-method
> ### sldaB,ExpressionSet,character,integer-method
> ### svmB,ExpressionSet,character,integer-method
> ### Keywords: classif
>
> ### ** Examples
>
> # access and trim an ExpressionSet
> library(golubEsets)
> data(Golub_Merge)
> smallG <- Golub_Merge[1:60,]
> # set a PRNG seed for reproducibilitiy
> set.seed(1234) # needed for nnet initialization
> # now run the classifiers
> knnB( smallG, "ALL.AML", 1:40 )
MLOutput instance, method= knn
Call:
knnB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL AML
25 7
summary of class assignment quality scores:
Min. 1st Qu. Median Mean 3rd Qu. Max.
1 1 1 1 1 1
> nnetB( smallG, "ALL.AML", 1:40, size=5, decay=.01 )
# weights: 311
initial value 34.887063
iter 10 value 23.023237
iter 20 value 22.682248
iter 30 value 22.457325
iter 40 value 21.954686
iter 50 value 21.315800
iter 60 value 20.914228
iter 70 value 20.695695
iter 80 value 20.614069
iter 90 value 19.198363
iter 100 value 17.709287
final value 17.709287
stopped after 100 iterations
MLOutput instance, method= nnet
a 60-5-1 network with 311 weights
inputs: AFFX.BioB.5_at AFFX.BioB.M_at AFFX.BioB.3_at AFFX.BioC.5_at AFFX.BioC.3_at AFFX.BioDn.5_at AFFX.BioDn.3_at AFFX.CreX.5_at AFFX.CreX.3_at AFFX.BioB.5_st AFFX.BioB.M_st AFFX.BioB.3_st AFFX.BioC.5_st AFFX.BioC.3_st AFFX.BioDn.5_st AFFX.BioDn.3_st AFFX.CreX.5_st AFFX.CreX.3_st hum_alu_at AFFX.DapX.5_at AFFX.DapX.M_at AFFX.DapX.3_at AFFX.LysX.5_at AFFX.LysX.M_at AFFX.LysX.3_at AFFX.PheX.5_at AFFX.PheX.M_at AFFX.PheX.3_at AFFX.ThrX.5_at AFFX.ThrX.M_at AFFX.ThrX.3_at AFFX.TrpnX.5_at AFFX.TrpnX.M_at AFFX.TrpnX.3_at AFFX.HUMISGF3A.M97935_5_at AFFX.HUMISGF3A.M97935_MA_at AFFX.HUMISGF3A.M97935_MB_at AFFX.HUMISGF3A.M97935_3_at AFFX.HUMRGE.M10098_5_at AFFX.HUMRGE.M10098_M_at AFFX.HUMRGE.M10098_3_at AFFX.HUMGAPDH.M33197_5_at AFFX.HUMGAPDH.M33197_M_at AFFX.HUMGAPDH.M33197_3_at AFFX.HSAC07.X00351_5_at AFFX.HSAC07.X00351_M_at AFFX.HSAC07.X00351_3_at AFFX.HUMTFRR.M11507_5_at AFFX.HUMTFRR.M11507_M_at AFFX.HUMTFRR.M11507_3_at AFFX.M27830_5_at AFFX.M27830_M_at AFFX.M27830_3_at AFFX.HSAC07.X00351_3_st AFFX.HUMGAPDH.M33197_5_st AFFX.HUMGAPDH.M33197_M_st AFFX.HUMGAPDH.M33197_3_st AFFX.HSAC07.X00351_5_st AFFX.HSAC07.X00351_M_st A28102_at
output(s): sampLab
options were - entropy fitting decay=0.01
Call:
nnetB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40,
size = 5, decay = 0.01)
predicted class distribution:
ALL AML
23 9
summary of class membership probabilities:
[,1]
Min. 0.01127
1st Qu. 0.07319
Median 0.07551
Mean 0.23300
3rd Qu. 0.61790
Max. 0.72640
> lvq1B( smallG, "ALL.AML", 1:40 )
MLOutput instance, method= lvq1
Call:
lvq1B(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL
32
> naiveBayesB( smallG, "ALL.AML", 1:40 )
MLOutput instance, method= naiveBayes
Call:
naiveBayesB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL AML
16 16
> svmB( smallG, "ALL.AML", 1:40 )
MLOutput instance, method= svm
Call:
svmB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL
32
> baggingB( smallG, "ALL.AML", 1:40 )
Loading required package: MASS
Attaching package: 'MASS'
The following object(s) are masked from package:genefilter :
area
Loading required package: mlbench
Loading required package: nnet
Loading required package: class
Attaching package: 'ipred'
The following object(s) are masked from package:genefilter :
cv
MLOutput instance, method= bagging
Call:
baggingB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL AML
28 4
> ipredknnB( smallG, "ALL.AML", 1:40 )
MLOutput instance, method= ipredknn
Call:
ipredknnB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL
32
summary of class assignment quality scores:
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.6 0.6 0.6 0.7 0.8 1.0
> sldaB( smallG, "ALL.AML", 1:40 )
MLOutput instance, method= slda
Call:
sldaB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL AML
31 1
summary of class membership probabilities:
ALL AML
Min. 0.4703 0.0462
1st Qu. 0.6843 0.1463
Median 0.7586 0.2414
Mean 0.7546 0.2454
3rd Qu. 0.8537 0.3157
Max. 0.9538 0.5297
> ldaB( smallG, "ALL.AML", 1:40 )
Warning in lda.default(x, grouping, ...) : variables are collinear
MLOutput instance, method= lda
Call:
ldaB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL AML
28 4
summary of class membership probabilities:
ALL AML
Min. 0.000643 1.762e-09
1st Qu. 0.886000 5.023e-04
Median 0.998400 1.600e-03
Mean 0.851600 1.484e-01
3rd Qu. 0.999500 1.140e-01
Max. 1.000000 9.994e-01
> qdaB( smallG[1:10,], "ALL.AML", 1:40 )
MLOutput instance, method= qda
Call:
qdaB(exprObj = smallG[1:10, ], classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL AML
22 10
summary of class membership probabilities:
ALL AML
Min. 6.831e-06 3.661e-21
1st Qu. 3.295e-01 1.332e-06
Median 9.942e-01 5.814e-03
Mean 7.035e-01 2.965e-01
3rd Qu. 1.000e+00 6.705e-01
Max. 1.000e+00 1.000e+00
> pamrB( smallG, "ALL.AML", 1:40 )
Loading required package: pamr
Loading required package: cluster
123456789101112131415161718192021222324252627282930MLOutput instance, method= pamr
Call:
pamrB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:40)
predicted class distribution:
ALL AML
31 1
dimensions of (threshold-based) class membership probabilities:
[1] 40 2 30
> rpartB( smallG, "ALL.AML", 1:35 )
MLOutput instance, method= rpart
Call:
rpartB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:35)
predicted class distribution:
ALL AML
23 14
> randomForestB( smallG, "ALL.AML", 1:35 )
MLOutput instance, method= randomForest
Call:
randomForestB(exprObj = smallG, classifLab = "ALL.AML", trainInd = 1:35)
predicted class distribution:
ALL AML
28 9
> gbmB( smallG, "ALL.AML", 1:40, n.minobsinnode=3 , n.trees=6000)
Loading required package: gbm
Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
there is no package called 'gbm'
Error in gbmB(smallG, "ALL.AML", 1:40, n.minobsinnode = 3, n.trees = 6000) :
could not find function "gbm.fit"
Execution halted
MLInterfaces.Rcheck/00install.out:
installing R.css in D:/biocbld/bbs-2.1-bioc/meat/MLInterfaces.Rcheck
---------- Making package MLInterfaces ------------
adding build stamp to DESCRIPTION
installing R files
preparing package MLInterfaces for lazy loading
Loading required package: Biobase
Loading required package: tools
Welcome to Bioconductor
Vignettes contain introductory material. To view, type
'openVignette()'. To cite Bioconductor, see
'citation("Biobase")' and for packages 'citation(pkgname)'.
Loading required package: genefilter
Loading required package: survival
Loading required package: splines
Loading required package: rpart
Loading required package: rda
installing inst files
installing man source files
installing indices
installing help
>>> Building/Updating help pages for package 'MLInterfaces'
Formats: text html latex example chm
MLIclust text html latex example chm
MLIntInternals text html latex example chm
MLearn-methods text html latex example chm
RAB text html latex example chm
SOMB text html latex example chm
classifOutput-class text html latex example chm
clustOutput-class text html latex example chm
confuMat-methods text html latex example chm
knnB text html latex example chm
planarPlot-methods text html latex example chm
raboostCont-class text html latex example chm
varImpStruct-class text html latex example chm
xval-methods text html latex example chm
xvalLoop-methods text html latex chm
xvalLoop text html latex example chm
Microsoft HTML Help Compiler 4.74.8702
Compiling d:\biocbld\bbs-2.1-bioc\meat\MLInterfaces.Rcheck\00_pkg_src\MLInterfaces\chm\MLInterfaces.chm
Compile time: 0 minutes, 0 seconds
16 Topics
245 Local links
0 Internet links
1 Graphic
Created d:\biocbld\bbs-2.1-bioc\meat\MLInterfaces.Rcheck\00_pkg_src\MLInterfaces\chm\MLInterfaces.chm, 47,787 bytes
Compression decreased file by 87,677 bytes.
adding MD5 sums
* DONE (MLInterfaces)