RPART explain the predict output for type matrix

Question

When I use the predict function of R(v 3.4.0) for classification tree as below it gives me an output with 10 columns.

p2 <- predict(mmodel,test_data,type = "matrix")

Output looks something like this:

    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]      [,10]
1       3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102
5       3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102
9       3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102
13      3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102
17      3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102
21      3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102
25      3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102
29      3    0    0   37    0  0.0 0.00 1.00  0.0 0.37755102

I want to know the descriptions of these columns (on what each column represent). I have 4 classes in the data set.

I'm not sure I understand what's given on RPART documentation on this.

If type = "matrix":

a matrix of the full responses (frame$yval2 if this exists, otherwise frame$yval). For regression trees, this is the mean response, for Poisson trees it is the response rate and the number of events at that node in the fitted tree, and for classification trees it is the concatenation of at least the predicted class, the class counts at that node in the fitted tree, and the class probabilities (some versions of rpart may contain further columns).

Answer 1

Col 1 : Level number

Cols 2-5 : 4 class frequencies

Cols 6-9 : 4 class probabilities

Col 10 : cases in that level over total number of cases (the quotient of 37 to 98 perhaps)