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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