On 18.02.2010 19:43, madhu sankar wrote:
Hi,
I am having trouble with svm regression.it is not giving the right results.
example
model<- svm(dataTrain,classTrain,type="eps-regression")
predict(model, dataTest)
36 37 38 39 40 41
42
-13.838257 -1.475401 10.502739 -3.047656 -8.713697 3.812873
1.741999
43 44 45 46 47 48
49
-6.034361 -13.469742 7.628642 -22.197060 -3.417444 -8.536890
-11.876133
50
-5.877457
My dataSet has 50 columns and 19 rows
my classSet has 50 columns and 1 row
My dataTrain has 35(1:35) columns and 19 rows
My classTrain has 35(1:35) columns and 1 row
My dataTest has 15(36:50) columns and 19 rows
My classTest has 15(36:50) columns and 1 row
Same problems as in my last mail:
I fear you are mixing up several things: regression vs. classification,
rows vs. columns....
My results should be as follows:
[1] -25.70 30.30 -58.50 -1.12 7.62 -16.10 -48.50 21.10 12.60 -43.00
[11] -47.30 -47.90 -38.40 -21.30 22.40
Why do you know?
Uwe Ligges
But instead i get the wrong values.can anyone help me with it.
Thanks,
Joji.
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