title: caret train glm training error - empty result
body: <p>I have a dataset with a number of binary predictors and binary outcome. I am trying to use logistic regression to predict the outcome and use caret package.</p>
  
  <p>For some reason, after training my model does not produce result, but finishes without any errors. However, when I train with cross-validation, I get the result.</p>
  
  <pre><code>&gt; Model = train(success ~ . - contestid - index - tags, data = p.train, 
  +               method = "glm",
  +               family = binomial(link = "logit"),
  +               trControl = trainControl(method = "none"));
  Warning message:
  glm.fit: fitted probabilities numerically 0 or 1 occurred 
  &gt; Model$results
  [1] Accuracy  Kappa     parameter
  &lt;0 rows&gt; (or 0-length row.names)
  </code></pre>
  
  <p>With cross-validation:</p>
  
  <pre><code>&gt; Model = train(success ~ . - contestid - index - tags, data = p.train, 
  +                 method = "glm",
  +                 family = binomial(link = "logit"),
  +                 trControl = trainControl(method = "cv"));
  There were 22 warnings (use warnings() to see them)
  &gt; Model$results
    parameter Accuracy     Kappa AccuracySD  KappaSD
  1      none      0.8 0.4208333  0.1972027 0.460482
  &gt; Model$resample
     Accuracy      Kappa Resample
  1      0.75  0.5000000   Fold01
  2      0.50  0.2000000   Fold02
  3      1.00  1.0000000   Fold03
  4      0.75  0.5000000   Fold04
  5      1.00  1.0000000   Fold05
  6      1.00         NA   Fold06
  7      0.75  0.5000000   Fold07
  8      0.75  0.0000000   Fold08
  9      0.50 -0.3333333   Fold09
  10     1.00         NA   Fold10
  </code></pre>
  
  <p>All warnings are the same, about the fitted probabilities, since my data allows perfect separation. However, this does not prevent training with cv to produce results.</p>
  
  <p>What might be the reason for the absence of results in the first case?</p>
  
  <p>Thanks</p>