Hello Steve
Thanks for quick responses its really helping me out .Ya I made the
necessary changes you had mentioned. I was not sure of that 'type' argument
where u had told me to set it to SVM . Do you mean I have to give that
argument in this line "cl <- c(c(rep("ALL",10), rep("AML",10)));" and when I
ran the code the following output I had got :
result:
pred ALL AML
ALL 7 5
AML 3 5
Does this mean that 7 samples of ALL from test file has been classified as
ALL and 5 samples of ALL are classified as AML and so on or is there any
other way we can interpret this result . I had done one more thing I had
taken the transpose of both my test and train files as given below:
model<- svm(t(train),cl);
pred <- predict(model,t(test));
And the result I had got is :
Result:
pred ALL AML
ALL 10 0
AML 0 10
why is there a difference in the result which I had given in the before
post?does this mean doing transpose classifies the samples better? or is
there any reason for this?
I am sorry I am troubling you a lot but seriously its a very timely help I
am really thankful to you.
-Aadhithya
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