title: ' Error in { : task 1 failed - "subscript out of bounds" '
body: <p>I am new to R and I am trying to run this code, but I always get this error: </p>
  
  <blockquote>
    <p>Error in { : task 1 failed - "subscript out of bounds"</p>
  </blockquote>
  
  <p>and this is the code I am running </p>
  
  <pre><code>svmFit &lt;- train(class ~., method = "svmLinear", data = teacher3,
              tuneLength = 7,
              trControl = trainControl(
                  method = "cv", indexOut = teacher3.train))
  </code></pre>
  
  <p>OR</p>
  
  <pre><code>C45Fit &lt;- train(class ~ ., method = "J48", data = teacher3,
  tuneLength = 5,
  trControl = trainControl(
      method = "cv", indexOut = teacher3.train))
  </code></pre>
  
  <p>OR</p>
  
  <pre><code>ctreeFit &lt;- train(class ~ ., method = "ctree", data = teacher3,
  tuneLength = 5,
  trControl = trainControl(
      method = "cv", indexOut = teacher3.train))
  </code></pre>
  
  <p>I already included all the needed packages and called them! but this error keep showing in all the Classifications </p>
  
  <p>This is a dput of my data set : </p>
  
  <pre><code>structure(list(native_speaker = structure(c(1L, 2L, 1L, 1L, 2L, 
  2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 
  2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 
  2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 
  2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
  2L, 2L), .Label = c("english speaker", "non-english speaker"), class = "factor"), 
      course_instructor = structure(c(12L, 19L, 12L, 5L, 14L, 12L, 
      20L, 22L, 13L, 19L, 22L, 6L, 10L, 9L, 9L, 9L, 14L, 13L, 6L, 
      14L, 4L, 4L, 3L, 15L, 19L, 14L, 2L, 1L, 18L, 13L, 23L, 10L, 
      6L, 6L, 5L, 17L, 25L, 5L, 1L, 12L, 19L, 12L, 5L, 14L, 12L, 
      20L, 22L, 13L, 19L, 22L, 6L, 10L, 9L, 9L, 9L, 14L, 13L, 6L, 
      14L, 4L, 4L, 3L, 15L, 19L, 14L, 2L, 1L, 18L, 13L, 23L, 10L, 
      6L, 6L, 5L, 17L, 25L, 5L, 1L, 12L, 6L, 17L, 20L, 6L, 10L, 
      13L, 14L, 12L, 12L, 12L, 1L, 21L, 20L, 10L, 21L, 15L, 15L, 
      23L, 13L, 20L, 6L, 9L, 12L, 12L, 9L, 13L, 8L, 12L, 8L, 12L, 
      6L, 22L, 14L, 1L, 2L, 11L, 2L, 19L, 12L, 3L, 19L, 8L, 6L, 
      20L, 22L, 1L, 6L, 2L, 8L, 13L, 10L, 8L, 21L, 1L, 16L, 20L, 
      11L, 20L, 13L, 14L, 22L, 12L, 21L, 17L, 7L, 24L, 12L, 7L, 
      22L, 10L, 13L, 3L), .Label = c("Agnes Gonzales", "Amber Waters", 
      "Amelia Gray", "Audrey Abbott", "Carla Hill", "Cesar Lynch", 
      "Derrick Johnson", "Donnie Hayes", "Elena Gordon", "Frank Barnes", 
      "Glenn Reynolds", "Herman Jensen", "Jonathan Mitchell", "Julian Brooks", 
      "Kristine Conner", "Lydia Maxwell", "Marianne Vega", "Marion Steele", 
      "Marlene Jones", "Marvin Klein", "Maurice Kennedy", "Pete Hicks", 
      "Ron Parks", "Ted Briggs", "Vernon Frank"), class = "factor"), 
      course = structure(c(22L, 22L, 22L, 21L, 14L, 22L, 16L, 22L, 
      22L, 22L, 9L, 4L, 18L, 19L, 19L, 19L, 14L, 22L, 22L, 7L, 
      23L, 23L, 10L, 1L, 14L, 14L, 22L, 1L, 21L, 22L, 4L, 16L, 
      4L, 22L, 21L, 24L, 12L, 21L, 1L, 22L, 22L, 22L, 21L, 14L, 
      22L, 16L, 22L, 22L, 22L, 9L, 4L, 18L, 19L, 19L, 19L, 14L, 
      22L, 22L, 7L, 23L, 23L, 10L, 1L, 14L, 14L, 22L, 1L, 21L, 
      22L, 4L, 16L, 4L, 22L, 21L, 24L, 12L, 21L, 1L, 22L, 22L, 
      6L, 21L, 22L, 18L, 22L, 14L, 22L, 22L, 22L, 9L, 19L, 16L, 
      7L, 19L, 1L, 24L, 12L, 14L, 21L, 4L, 19L, 22L, 22L, 19L, 
      22L, 21L, 22L, 21L, 22L, 4L, 22L, 14L, 1L, 22L, 23L, 23L, 
      4L, 22L, 10L, 4L, 21L, 17L, 3L, 22L, 1L, 4L, 22L, 21L, 4L, 
      5L, 1L, 2L, 14L, 8L, 15L, 24L, 3L, 4L, 14L, 22L, 22L, 2L, 
      11L, 21L, 13L, 22L, 21L, 22L, 23L, 4L, 20L), .Label = c("Applied Multivariate Analysis", 
      "Basic Applied Statistics", "Basic Probability Theory", "Basic Statistics for Economics", 
      "Caclulus I", "Computing and Graphics in Applied Statistics", 
      "english I", "english II", "Independent Studies in Statistics", 
      "Intermediate Statistical Analysis", "Introduction to Experimental Design", 
      "Introduction to Sampling", "Introductory Statistics for Business", 
      "Level II Statistics", "Level III Statistics. ", "Managerial Statistics", 
      "Regression Methods", "Reliability-Quality Control", "Statistical Quality Control", 
      "Statistics for Social Work", "Statistics I", "Statistics II", 
      "Theory of Probability", "Theory of Statistics"), class = "factor"), 
      season = structure(c(2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 
      2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 
      1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 
      2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 
      1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("regular", "summer"
      ), class = "factor"), class_size = c(19L, 17L, 49L, 33L, 
      55L, 20L, 19L, 27L, 58L, 20L, 9L, 30L, 29L, 39L, 42L, 43L, 
      10L, 46L, 10L, 42L, 27L, 23L, 31L, 22L, 37L, 13L, 24L, 38L, 
      42L, 28L, 51L, 19L, 31L, 13L, 37L, 36L, 21L, 48L, 38L, 19L, 
      17L, 49L, 33L, 55L, 20L, 19L, 27L, 58L, 20L, 9L, 30L, 29L, 
      39L, 42L, 43L, 10L, 46L, 10L, 42L, 27L, 23L, 31L, 22L, 37L, 
      13L, 24L, 38L, 42L, 28L, 51L, 19L, 31L, 13L, 37L, 36L, 21L, 
      48L, 38L, 25L, 17L, 11L, 39L, 11L, 19L, 45L, 20L, 20L, 20L, 
      38L, 17L, 19L, 24L, 25L, 31L, 31L, 18L, 22L, 27L, 14L, 20L, 
      35L, 20L, 20L, 37L, 15L, 25L, 10L, 14L, 38L, 29L, 19L, 30L, 
      32L, 27L, 34L, 23L, 66L, 12L, 29L, 19L, 3L, 17L, 7L, 21L, 
      36L, 54L, 29L, 45L, 11L, 16L, 18L, 44L, 17L, 21L, 20L, 24L, 
      5L, 42L, 30L, 19L, 11L, 29L, 15L, 37L, 10L, 24L, 26L, 12L, 
      48L, 51L, 27L), class = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
      3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
      2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
      3L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 
      1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 
      3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 
      2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 
      1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 
      2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("high", 
      "low", "medium"), class = "factor")), .Names = c("native_speaker", 
  "course_instructor", "course", "season", "class_size", "class"
  ), class = "data.frame", row.names = c(NA, -151L))
  </code></pre>