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Click here to access the train and test data I used. I m new to SVM. I was trying the svm package in R to train my data which consists of 40 attributes and 39 labels. All attributes are of double type(most of them are 0's or 1's becuase I performed dummy encoding on the categorical attriubutes ) , the class label was of different strings which i later converted to a factor and its now of Integer type. 

model=svm(Category~.,data=train1,scale=FALSE)
p1=predict(model,test1,"prob")

This was the result i got once i trained the model using SVM.

Call:
svm(formula = Category ~ ., data = train1, scale = FALSE)
Parameters:
   SVM-Type:  C-classification 
   SVM-Kernel:  radial 
   cost:  1 
  gamma:  0.02564103 

   Number of Support Vectors:  2230

I used the predict function

Error in predict.svm(model, test1, "prob") : 
NAs in foreign function call (arg 1)
In addition: Warning message:
In predict.svm(model, test1, "prob") : NAs introduced by coercion

I'm not understanding why this error is appearing, I checked all attributes of my training data none of them have NA's in them. Please help me with this. Thanks

Sujith Shivaprakash
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  • You should provide a [reproducible example](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) that contains sample data to reproduce the error. The problem is likely with your data but that's the part you haven't shown so it's difficult to say what might be wrong. – MrFlick Apr 04 '16 at 02:07
  • I added the data set and the code. Please review it. – Sujith Shivaprakash Apr 04 '16 at 03:30

1 Answers1

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I'm assuming you are using the package e1071 (you don't specify which package are you using, and as far as I know there is no package called svm).

The error message is confusing, but the problem is that you are passing "prob" as the 3rd argument, while the function expects a boolean. Try it like this:

require(e1071)
model=svm(Category~.,data=train1, scale=FALSE, probability=TRUE)
p1=predict(model,test1, probability = TRUE)
head(attr(p1, "probabilities"))

This is a sample of the output I get.

  WARRANTS OTHER OFFENSES LARCENY/THEFT VEHICLE THEFT  VANDALISM NON-CRIMINAL    ROBBERY    ASSAULT WEAPON LAWS   BURGLARY
1 0.04809877      0.1749634     0.2649921    0.02899535 0.03548131    0.1276913 0.02498949 0.08322866  0.01097913 0.03800846
  SUSPICIOUS OCC DRUNKENNESS FORGERY/COUNTERFEITING DRUG/NARCOTIC STOLEN PROPERTY SECONDARY CODES    TRESPASS MISSING PERSON
1 0.03255891     0.003790755   0.006249521    0.01944938     0.004843043      0.01305858 0.009727582     0.01840337
     FRAUD  KIDNAPPING     RUNAWAY DRIVING UNDER THE INFLUENCE SEX OFFENSES FORCIBLE PROSTITUTION DISORDERLY CONDUCT       ARSON
1 0.01884472 0.006089563 0.001378799                 0.003289503            0.01071418  0.004562048        0.003107619 0.002124643
  FAMILY OFFENSES LIQUOR LAWS      BRIBERY EMBEZZLEMENT      SUICIDE
1    0.0004787845 0.001669914 0.0007471968 0.0007465053 0.0007374036

Hope it helps.

lrnzcig
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