CRAN Package Check Results for Package hyperSMURF

Last updated on 2018-04-05 16:50:23 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.1.4 4.66 57.10 61.76 ERROR
r-devel-linux-x86_64-debian-gcc 1.1.4 4.60 51.70 56.30 ERROR
r-devel-linux-x86_64-fedora-clang 1.1.4 124.51 OK
r-devel-linux-x86_64-fedora-gcc 1.1.4 116.44 OK
r-devel-windows-ix86+x86_64 1.1.4 14.00 89.00 103.00 OK
r-devel-osx-x86_64 1.1.4 OK
r-patched-linux-x86_64 1.1.4 3.86 62.88 66.74 ERROR
r-patched-solaris-x86 1.1.4 192.60 OK
r-release-linux-x86_64 1.1.4 4.61 88.86 93.47 OK
r-release-windows-ix86+x86_64 1.1.4 17.00 119.00 136.00 OK
r-release-osx-x86_64 1.1.4 OK
r-oldrel-windows-ix86+x86_64 1.1.4 12.00 111.00 123.00 OK

Check Details

Version: 1.1.4
Check: examples
Result: ERROR
    Running examples in ‘hyperSMURF-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: hyperSMURF.corr.cv.parallel
    > ### Title: hyperSMURF cross-validation with embedded correlation-based
    > ### feature selection
    > ### Aliases: hyperSMURF.corr.cv.parallel
    >
    > ### ** Examples
    >
    > d <- imbalanced.data.generator(n.pos=10, n.neg=160, n.features=7,
    + n.inf.features=1, sd=0.3, seed=1);
    > if (Sys.info()['sysname']!="Windows")
    + res<-hyperSMURF.corr.cv.parallel (d$data, d$labels, kk=2, n.part=2, fp=1, ratio=1, k=1,
    + ntree=5, mtry=2, n.feature=3, seed = 1, fold.partition=NULL, ncores=2, file="");
    Creating new folds
    Starting preparation data for Fold 1 ...
    Starting feature selection on Fold 1 ...
    Selected features :
     1 5 4
    Starting training on Fold 1 ...
    randomForest 4.6-14
    Type rfNews() to see new features/changes/bug fixes.
    Training of ensemble 1 started
    Warning in rm(data.train) : object 'data.train' not found
    Training of ensemble 2 started
    Warning in rm(data.train) : object 'data.train' not found
    Error in sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) :
     write error, closing pipe to the master
    Calls: hyperSMURF.corr.cv.parallel ... <Anonymous> -> mclapply -> lapply -> FUN -> sendMaster
    Starting test on Fold 1 ...
    Error in { :
     task 1 failed - "no applicable method for 'predict' applied to an object of class "NULL""
    Calls: hyperSMURF.corr.cv.parallel -> hyperSMURF.test.parallel -> %dopar% -> <Anonymous>
    Execution halted
Flavor: r-devel-linux-x86_64-debian-clang

Version: 1.1.4
Check: examples
Result: ERROR
    Running examples in ‘hyperSMURF-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: hyperSMURF.corr.cv.parallel
    > ### Title: hyperSMURF cross-validation with embedded correlation-based
    > ### feature selection
    > ### Aliases: hyperSMURF.corr.cv.parallel
    >
    > ### ** Examples
    >
    > d <- imbalanced.data.generator(n.pos=10, n.neg=160, n.features=7,
    + n.inf.features=1, sd=0.3, seed=1);
    > if (Sys.info()['sysname']!="Windows")
    + res<-hyperSMURF.corr.cv.parallel (d$data, d$labels, kk=2, n.part=2, fp=1, ratio=1, k=1,
    + ntree=5, mtry=2, n.feature=3, seed = 1, fold.partition=NULL, ncores=2, file="");
    Creating new folds
    Starting preparation data for Fold 1 ...
    Starting feature selection on Fold 1 ...
    Selected features :
     1 5 4
    Starting training on Fold 1 ...
    randomForest 4.6-14
    Type rfNews() to see new features/changes/bug fixes.
    Training of ensemble 2 started
    Warning in rm(data.train) : object 'data.train' not found
    Training of ensemble 1 started
    Warning in rm(data.train) : object 'data.train' not found
    Error in sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE)) :
     write error, closing pipe to the master
    Calls: hyperSMURF.corr.cv.parallel ... <Anonymous> -> mclapply -> lapply -> FUN -> sendMaster
    Starting test on Fold 1 ...
    Error in { :
     task 1 failed - "no applicable method for 'predict' applied to an object of class "NULL""
    Calls: hyperSMURF.corr.cv.parallel -> hyperSMURF.test.parallel -> %dopar% -> <Anonymous>
    Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc

Version: 1.1.4
Check: examples
Result: ERROR
    Running examples in ‘hyperSMURF-Ex.R’ failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: hyperSMURF.corr.cv.parallel
    > ### Title: hyperSMURF cross-validation with embedded correlation-based
    > ### feature selection
    > ### Aliases: hyperSMURF.corr.cv.parallel
    >
    > ### ** Examples
    >
    > d <- imbalanced.data.generator(n.pos=10, n.neg=160, n.features=7,
    + n.inf.features=1, sd=0.3, seed=1);
    > if (Sys.info()['sysname']!="Windows")
    + res<-hyperSMURF.corr.cv.parallel (d$data, d$labels, kk=2, n.part=2, fp=1, ratio=1, k=1,
    + ntree=5, mtry=2, n.feature=3, seed = 1, fold.partition=NULL, ncores=2, file="");
    Creating new folds
    Starting preparation data for Fold 1 ...
    Starting feature selection on Fold 1 ...
    Selected features :
     1 5 4
    Starting training on Fold 1 ...
    randomForest 4.6-14
    Type rfNews() to see new features/changes/bug fixes.
    Training of ensemble 1 started
    Warning in rm(data.train) : object 'data.train' not found
    Training of ensemble 2 started
    Warning in rm(data.train) : object 'data.train' not found
    Starting test on Fold 1 ...
    Error in { :
     task 1 failed - "no applicable method for 'predict' applied to an object of class "NULL""
    Calls: hyperSMURF.corr.cv.parallel -> hyperSMURF.test.parallel -> %dopar% -> <Anonymous>
    Execution halted
Flavor: r-patched-linux-x86_64