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I am new to R and I am trying to run this code, but I always get this error:

Error in { : task 1 failed - "subscript out of bounds"

and this is the code I am running 

svmFit <- train(class ~., method = "svmLinear", data = teacher3,
            tuneLength = 7,
            trControl = trainControl(
                method = "cv", indexOut = teacher3.train))

OR

C45Fit <- train(class ~ ., method = "J48", data = teacher3,
tuneLength = 5,
trControl = trainControl(
    method = "cv", indexOut = teacher3.train))

OR

ctreeFit <- train(class ~ ., method = "ctree", data = teacher3,
tuneLength = 5,
trControl = trainControl(
    method = "cv", indexOut = teacher3.train))

I already included all the needed packages and called them! but this error keep showing in all the Classifications

This is a dput of my data set : 

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))
Has QUIT--Anony-Mousse
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    Please edit with the results of `dput(teacher3)` (or a representative subset) instead of a picture. – alistaire Jan 28 '16 at 03:04
  • This might help: http://stackoverflow.com/questions/15031338/subscript-out-of-bounds-general-definition-and-solution – Sotos Jan 28 '16 at 07:35
  • The scripts work without the indexout option. Since we don't have teacher3.train it is a bit difficult to say where the error lies. Check if the length of teacher3.train is the same as the number of records in teacher3. Also make sure you have the latest version of caret. – phiver Jan 28 '16 at 07:51

0 Answers0