Thanks Oldrich and Max,
I have some more queries.
If I need to train svm() with only one instance I get the following error:
Error in if (any(co)) { : missing value where TRUE/FALSE needed
Will it be wiser if I duplicate the instance with minute changes in the values,
or there is some other way
On Mar 7, 2008, at 2:17 AM, Oldrich Kruza wrote:
Hello Soumyadeep,
if you store the data in a tabular file, then I suggest using standard
text-editing tools like cut (say your file is called data.csv, fields
are separated with commas and you want to get rid of the third and
sixth column):
Also, see the nearZeroVar function in the caret package.
MAx
On Fri, Mar 7, 2008 at 7:41 AM, Charilaos Skiadas [EMAIL PROTECTED] wrote:
On Mar 7, 2008, at 2:17 AM, Oldrich Kruza wrote:
Hello Soumyadeep,
if you store the data in a tabular file, then I suggest using standard
What should I do if I need to train svm() with data having same value across
all rows in some columns. These must be the important features of the class and
we cant exclude these columns to build up models.
The error I am getting is:
Error in predict.svm(ret, xhold) : Model is empty!
In
A rather technical workaround I see could be adding a row with a
different value. But if a column only ever has one value, then it
contributes nothing to the model and I see no reason why it would have
to be kept.
~ Oldrich Kruza
On Fri, Mar 7, 2008 at 6:45 AM, Soumyadeep nandi
[EMAIL PROTECTED]
Thanks Oldrich,
Actually I was not sure if I can remove these columns and build model. Thanks
a lot for your kind suggestion. Could you tell me if there any function to
remove these columns from the data matrix.
With best regards,
Soumyadeep
Oldrich Kruza [EMAIL PROTECTED] wrote: A rather
Hello Soumyadeep,
if you store the data in a tabular file, then I suggest using standard
text-editing tools like cut (say your file is called data.csv, fields
are separated with commas and you want to get rid of the third and
sixth column):
$ cut --complement --delimiter=, --fields=3,6 data.csv
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