title: R SVM return NA for predictions with missing data
body: <p>I am attempting to make predictions using a trained SVM from package e1071 but my data contains some missing values (NA).</p>
  
  <p>I would like the returned predictions to be NA when that instance has any missing values. I tried to use na.action = na.pass as below but it gives me an error "Error in names(ret2) &lt;- rowns : 'names' attribute [150] must be the same length as the vector [149]".</p>
  
  <p>If I use na.omit then I can get predictions without instances with missing data.
  How can I get predictions including NAs?</p>
  
  <pre><code>library(e1071)
  model &lt;- svm(Species ~ ., data = iris)
  print(length(predict(model, iris)))
  tmp &lt;- iris
  tmp[1, "Sepal.Length"] &lt;- NA
  print(length(predict(model, tmp, na.action = na.pass)))
  </code></pre>