title: caret coefficients of cross validated set
body: <p>Is it possible to get the coefficients of all the cross validation set from R Caret package?</p>
  
  <pre><code>set.seed(1)
  mu &lt;- rep(0, 4)
  Sigma &lt;- matrix(.7, nrow=4, ncol=4) 
  diag(Sigma)  &lt;-  1
  rawvars &lt;- mvrnorm(n=1000, mu=mu, Sigma=Sigma)
  d  &lt;- as.ordered( 
    as.numeric(rawvars[,1]&gt;0.5) )
  d[1:200]  &lt;- 1
  df  &lt;- data.frame(rawvars, d)
  ind  &lt;- sample(1:nrow(df), 500)
  train  &lt;- df[ind,]
  test  &lt;- df[-ind,]
  trControl  &lt;- trainControl(method = "repeatedcv",
                             repeats = 1,
                             classProb = T,
                             summaryFunction= twoClassSummary)
  fit.caret  &lt;- train(d~., data=train,
                      method="glm",
                      family = binomial(link="probit"), trControl =trControl)
  &gt; fit.caret$resample
           ROC      Sens      Spec    Resample
  1  0.8383838 0.8148148 0.7272727 Fold01.Rep1
  2  0.8881988 0.8571429 0.7391304 Fold02.Rep1
  3  0.8937198 0.8518519 0.7826087 Fold03.Rep1
  4  0.8792271 0.7407407 0.8260870 Fold04.Rep1
  5  0.8771044 0.8888889 0.7727273 Fold05.Rep1
  6  0.8703704 0.6666667 0.7727273 Fold06.Rep1
  7  0.9145963 0.8928571 0.8260870 Fold07.Rep1
  8  0.8649068 0.6785714 0.8260870 Fold08.Rep1
  9  0.8084416 0.8928571 0.6818182 Fold09.Rep1
  10 0.7938312 0.7857143 0.6363636 Fold10.Rep1
  </code></pre>
  
  <p>I have the ROCs for each repetition, but I also need coefficients for each run</p>