title: Error using Caret Package for Random Forest (Regression)
body: <p>So, I am trying to train a model and test it using a random forest regression. My response variable is a numeric and I have 23 other variables which are a mix of numeric and characters. I am using the following block of code:</p>
  
  <pre><code>library(e1071)
  library(dplyr)
  library(class)
  library(caret)
  library(kernlab)
  
  data=read.csv(choose.files())
  
  
  set.seed(1)
  mydata=data
  n=dim(mydata)[1]
  p=dim(mydata)[2]-1
  x=mydata[,-3]
  y=mydata[,3]
  
  n_train=35
  n_test=9
  
  random_order=sample(n)
  test_index=random_order[1:n_test]
  train_index=random_order[-(1:n_test)]
  y_train=y[train_index]
  y_test=y[test_index]
  x_train=x[train_index,]
  x_test=x[test_index,]
  
  traindata=data.frame(x=x_train,y=(y_train))
  testdata = data.frame(x=x_test,y=(y_test))
  
  fitControl &lt;- trainControl(## 10-fold CV
    method = "repeatedcv",classProbs=TRUE, 
    number = 10,
    ## repeated ten times
    repeats = 10)
  
  set.seed(1)
  newrf=train(y ~ ., data = traindata , method = "rf", 
               trControl = fitControl)
  
  newrf 
  bestmodel_rf= newrf$finalModel
  ypredcaret=predict(bestmodel_rf, newdata = testdata)
  table(predict=ypredcaret, truth=y_test)
  plot(newrf)
  bestmodel_rf
  </code></pre>
  
  <p>I am getting the following error:</p>
  
  <p>Warning message:
  In train.default(x, y, weights = w, ...) :
    cannnot compute class probabilities for regression
  Warning message:
  In train.default(x, y, weights = w, ...) :
    cannnot compute class probabilities for regression</p>