Hi. I am trying to construct a svmLinear model using the "caret" package
(see code below). Using the same data, without changing any setting,
sometimes it constructs the model successfully, and sometimes I get an index
out of bounds error. Is this unexpected behaviour? I would appreciate any
insights this issue.
Thanks.
~Kendric
> train.y
[1] S S S S R R R R R R R R R R R R R R R R R R R R
Levels: R S
> train.x
m1 m2
1 0.1756 0.6502
2 0.1110 -0.2217
3 0.0837 -0.1809
4 -0.3703 -0.2476
5 8.3825 2.8814
6 5.6400 12.9922
7 7.5537 7.4809
8 3.5005 5.7844
9 16.8541 16.6326
10 9.1851 8.7814
11 1.4405 11.0132
12 9.8795 2.6182
13 8.7151 4.5476
14 -0.2092 -0.7601
15 3.6876 2.5772
16 8.3776 5.0882
17 8.6567 7.2640
18 20.9386 20.1107
19 12.2903 4.7864
20 10.5920 7.5204
21 10.2679 9.5493
22 6.2023 11.2333
23 -5.0720 -4.8701
24 6.6417 11.5139
> svmLinearGrid <- expand.grid(.C=0.1)
> svmLinearFit <- train(train.x, train.y, method="svmLinear",
tuneGrid=svmLinearGrid)
Fitting: C=0.1
Error in indexes[[j]] : subscript out of bounds
> svmLinearFit <- train(train.x, train.y, method="svmLinear",
tuneGrid=svmLinearGrid)
Fitting: C=0.1
maximum number of iterations reached 0.0005031579 0.0005026807maximum number
of iterations reached 0.0002505857 0.0002506714Error in indexes[[j]] :
subscript out of bounds
> svmLinearFit <- train(train.x, train.y, method="svmLinear",
tuneGrid=svmLinearGrid)
Fitting: C=0.1
maximum number of iterations reached 0.0003270061 0.0003269764maximum number
of iterations reached 7.887867e-05 7.866367e-05maximum number of iterations
reached 0.0004087571 0.0004087466Aggregating results
Selecting tuning parameters
Fitting model on full training set
R version 2.11.1 (2010-05-31)
x86_64-redhat-linux-gnu
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=C LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] splines stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] kernlab_0.9-12 pamr_1.47 survival_2.35-8 cluster_1.12.3
[5] e1071_1.5-24 class_7.3-2 caret_4.70 reshape_0.8.3
[9] plyr_1.2.1 lattice_0.18-8
loaded via a namespace (and not attached):
[1] grid_2.11.1
--
MSc. Candidate
CIHR/MSFHR Training Program in Bioinformatics
University of British Columbia
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