All,
I am beginner in R here.I am working on SVM and am getting the below errors wheneverI call the predict function.I have tried reading the manual for predict() butI  am totally stumped and not able to move further.

> pred <- predict(model, Test[,-1])Error in scale(newdata[, object$scaled, drop = FALSE], center = object$x.scale$"scaled:center",  :   (subscript) logical subscript too long    The actual data sets are very huge , hence I am replicating it on a smaller basis.  My dataset contains lots of 'NA' values.
  The code I am calling is   > TrainingSet <- read.csv('TrainA.csv',header=TRUE)> TestingSet <- read.csv('TestA.csv',header=TRUE)
> Train <- subset(TrainingSet, select=c(-Class)) > Train_Class <- subset(TrainingSet, select=Class)
> Test <- subset(TestingSet, select=c(-Class))> Test_Class <- subset(TestingSet, select=Class)
> model <- svm(Train[,-1], Train_Class, kernel="linear", cross=10, na.action=na.omit)> model
Call:svm.default(x = Train[, -1], y = Train_Class, kernel = "linear", cross = 10, na.action = na.omit)

Parameters:   SVM-Type:  eps-regression  SVM-Kernel:  linear        cost:  1       gamma:  0.3333333     epsilon:  0.1 

Number of Support Vectors:  18
> Class <- Test_Class$Class> pred <- predict(model, Test[,-1])Error in scale(newdata[, object$scaled, drop = FALSE], center = object$x.scale$"scaled:center",  :   (subscript) logical subscript too long
    Training data set:
Gene_Symbol	Class	Subj-1	Subj-2	Subj-313CDNA73	0	0.225	-0.378	0.92720D7-FC4	0	1.668	1.762	1.445384D8-2	0	0.52	-1.019	1.58854TM	0	3.094	5.114	2.7435T4	0	-1.138	1.158	0.0176P	0	1.588	-2.541	-1.023A	0	-0.649	-1.884	1.253A2LP	0	1.765	3.75	-0.259AAMP	0	-1.133	-0.309	-1.557AARS	1	3.132	0.432	2.4AB026190	1	-0.244	-0.06	-0.021ABCA3	1	-0.003	-1.673	1.272ABCA4	1	-1.017	-0.493	-0.751ABCA5	1	3.319	3.234	0.503ABCA6	1	2.692	0.039	4.017ABCB1	1	0.362	-0.362	0.862ABCB10	1	0.028	-1.962	-0.795ABCC1	1	1.963	3.475	0.202ABCC2	1	-0.942	-3.496	0.297


  Test  Gene_Symbol	Class	Subj-1	Subj-2RBP3	0	-0.762	-1.132RBP4	0	0.494	3.802RBPMS	0	-0.311	0.612RBSK	0	-0.759	1.206RBX1	0	0.047	-0.31RCD-8	0	-0.42	-3.001RCL	1	-0.388	1.046RCN1	1	0.476	-1.092RCN2	1	-0.469	-0.707RCV1	1	-2.071	-0.854RDBP	1	0.904	1.325RDC1	1	1.668	1.905REA	1	0.09	-0.531RECQL	1	-1.957	-2.481
Any pointers on how to deal with the error would be greatly appreciated.ThanksSavitha

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