title: Is there a way to see False Negative rows?
body: <p>I have a data frame, split into train and test data sets, run svm, predict and confusion matrix functions.</p>
  <p>How can I see which rows are False Positive and False Negative?</p>
  <pre><code>Data_7c&lt;- Data_7G[, c(6, 15:18)] 
  split = sample.split(Data_7c$F, SplitRatio = 0.70)
  train = subset(Data_7c, split == TRUE)
  test = subset(Data_7c, split == FALSE)
  
  data1 = svm(F ~., data = train, method=&quot;C-classification&quot;, kernel=&quot;radial&quot;, cost = 1, gamma=0.001, scale = FALSE)
  pred1 &lt;- predict(data1, task = bh.task,newdata = test)
  head(as.data.frame(pred1))
  SVMcf1 &lt;- confusionMatrix(pred1, as.factor(test[,1]), positive = &quot;1&quot;)
  SVMcf1$table
  
  Confusion Matrix and Statistics
  
            Reference
  Prediction    0    1
           0 2203  146
           1    3    2
  
  </code></pre>
  <p>Data <code>test$F[1:20]</code> and <code>pred1[1:20]</code>:</p>
  <pre><code>structure(c(1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L), .Label = c(&quot;0&quot;, &quot;1&quot;), class = &quot;factor&quot;) 
  
  structure(c(`2` = 1L, `3` = 1L, `8` = 1L, `19` = 1L, `22` = 1L, 
  `25` = 1L, `40` = 1L, `49` = 1L, `51` = 1L, `55` = 1L, `57` = 1L, 
  `60` = 1L, `62` = 1L, `63` = 1L, `67` = 2L, `72` = 1L, `75` = 1L, 
  `80` = 1L, `81` = 1L, `89` = 1L), .Label = c(&quot;0&quot;, &quot;1&quot;), class = &quot;factor&quot;)
  </code></pre>