Hi,
I have a question on using svm{e1071} for a classification task:

No matter how I split the data into training and test, I always end with a
perfect accuracy in training but sensitivity = 0 for test. One example is
like this
      1   2
  1 209   0
  2   0  67

   pred1
     1  2
  1 47  0
  2 17  0

My question is, is there anything wrong with the following call:
m2 <- best.svm(class~., data=x1, gamma=2^(-3:3), cost=2^(0:5)) # x1 is
training data
pred1 <- predict(m2, x3)  # x3 is test data

Thanks!

-- 

Weiwei Shi, Ph.D
Research Scientist
GeneGO, Inc.

"Did you always know?"
"No, I did not. But I believed..."
---Matrix III

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