[R] RandomForest ... Always Returning a 1?

[apresley]

We have a pretty simple R forecasting problem, using randomForest.  Our
script is below.  We have data with about 6 columns, and 625 rows to do the
training on, and then we're trying to forecast 90 or so rows.

The x matrix has 3 years worth of sales data, starting at 6:15am.  However,
for some reason, it's always returning a "1", when predicting any data.

I've tried removing the first two columns, and the last column, which will
always be the same for both the predicted and training data.  That gets me a
mix of 1's and 2's.

If I do a regression, it's a little better, but only has a range of about
2.4 -> 5 ... whereas the original data is a wide range / variance, of
anywhere from 1 to 30.

What can I do to get some variance into this returned data?


library ('randomForest');

x <- matrix(data =
c(6,15,4,23,6,26,6,15,5,2,7,26,6,15,8,10,1,26,6,15,1,30,6,26,6,15,11,26,6,26,6,15,8,1,1,26,6,15,6,5,5,26,6,15,11,5,4,26,6,15,6,28,1,26,6,15,6,25,5,26,6,15,5,7,4,26,6,15,9,17,5,26,6,15,10,6,3,26,6,15,7,28,3,26,6,15,1,15,6,26,6,15,4,22,4,26,6,15,3,28,1,26,6,15,7,29,4,26,6,15,12,1,4,26,6,15,12,14,3,26,6,15,9,9,4,26,6,15,2,18,5,26,6,15,9,11,7,26,6,15,6,17,5,26,6,15,10,15,6,26,6,15,8,2,1,26,6,15,3,8,2,26,6,15,5,6,4,26,6,15,10,7,5,26,6,15,2,23,2,26,6,15,8,15,7,26,6,15,5,26,3,26,6,15,3,16,3,26,6,15,1,12,2,26,6,15,3,15,2,26,6,15,5,21,4,26,6,15,10,30,6,26,6,15,11,4,5,26,6,15,10,27,4,26,6,15,9,30,4,26,6,15,6,14,2,26,6,15,5,16,6,26,6,15,11,6,5,26,6,15,11,7,7,26,6,15,7,9,6,26,6,15,12,31,4,26,6,15,9,13,1,26,6,15,9,27,2,26,6,15,9,18,6,26,6,15,12,7,1,26,6,15,12,5,6,26,6,15,9,6,1,26,6,15,1,13,3,26,6,15,10,29,4,26,6,15,5,14,6,26,6,15,8,26,4,26,6,15,9,5,7,26,6,15,1,10,7,26,6,15,9,24,6,26,6,15,10,9,6,26,6,15,6,12,5,26,6,15,11,13,6,26,6,15,8,18,4,26,6,15,2,15,1,26,6,15,3,25,5,26,6,15,6,23,3,26,6,15,6,15,1,26,6,15,10,10,1,26,6,15,7,26,7,26,6,15,5,3,1,26,6,15,6,13,7,26,6,15,12,14,2,26,6,15,12,8,3,26,6,15,4,20,3,26,6,15,4,16,5,26,6,15,8,7,5,26,6,15,10,28,3,26,6,15,5,11,2,26,6,15,7,23,5,26,6,15,12,14,1,26,6,15,12,4,7,26,6,15,5,23,6,26,6,15,9,7,2,26,6,15,11,10,4,26,6,15,8,19,5,26,6,15,8,30,2,26,6,15,7,5,7,26,6,15,3,27,6,26,6,15,2,7,1,26,6,15,8,8,6,26,6,15,7,12,2,26,6,15,10,4,2,26,6,15,6,9,3,26,6,15,3,19,6,26,6,15,12,19,6,26,6,15,8,18,3,26,6,15,6,14,7,26,6,15,9,16,5,26,6,15,7,11,6,26,6,15,7,31,6,26,6,15,4,9,5,26,6,15,10,25,2,26,6,15,11,7,1,26,6,15,12,31,6,26,6,15,9,13,2,26,6,15,8,13,6,26,6,15,2,4,5,26,6,15,6,1,1,26,6,15,6,20,1,26,6,15,12,12,1,26,6,15,5,28,6,26,6,15,9,8,4,26,6,15,8,11,4,26,6,15,9,15,3,26,6,15,11,28,1,26,6,15,9,25,5,26,6,15,11,11,4,26,6,15,8,30,7,26,6,15,7,28,2,26,6,15,2,26,6,26,6,15,4,18,1,26,6,15,1,4,2,26,6,15,10,2,5,26,6,15,6,19,6,26,6,15,3,10,4,26,6,15,1,13,4,26,6,15,7,7,2,26,6,15,12,18,6,26,6,15,6,18,5,26,6,15,10,7,3,26,6,15,9,30,5,26,6,15,5,10,2,26,6,15,6,24,5,26,6,15,12,23,4,26,6,15,9,15,2,26,6,15,11,14,1,26,6,15,6,19,5,26,6,15,9,27,1,26,6,15,7,12,1,26,6,15,10,7,4,26,6,15,8,19,3,26,6,15,7,24,5,26,6,15,8,20,4,26,6,15,11,20,5,26,6,15,3,7,7,26,6,15,7,19,7,26,6,15,2,5,5,26,6,15,9,8,2,26,6,15,11,2,1,26,6,15,2,21,1,26,6,15,9,18,5,26,6,15,9,1,3,26,6,15,3,5,6,26,6,15,5,27,4,26,6,15,12,17,4,26,6,15,8,17,3,26,6,15,7,20,2,26,6,15,7,21,4,26,6,15,3,29,2,26,6,15,3,10,3,26,6,15,1,16,6,26,6,15,3,24,4,26,6,15,3,14,7,26,6,15,11,6,6,26,6,15,6,19,7,26,6,15,6,2,2,26,6,15,5,17,1,26,6,15,9,3,4,26,6,15,6,26,7,26,6,15,8,13,5,26,6,15,11,14,7,26,6,15,8,31,2,26,6,15,7,4,7,26,6,15,6,1,2,26,6,15,12,2,5,26,6,15,4,10,6,26,6,15,3,12,5,26,6,15,10,13,2,26,6,15,2,19,5,26,6,15,6,15,2,26,6,15,11,26,4,26,6,15,12,15,3,26,6,15,5,9,7,26,6,15,12,13,2,26,6,15,6,8,1,26,6,15,3,20,7,26,6,15,11,4,4,26,6,15,6,20,7,26,6,15,12,3,4,26,6,15,6,30,3,26,6,15,8,5,4,26,6,15,9,25,6,26,6,15,6,27,1,26,6,15,3,3,4,26,6,15,6,21,2,26,6,15,8,29,7,26,6,15,7,29,3,26,6,15,6,23,2,26,6,15,2,27,6,26,6,15,4,19,2,26,6,15,1,12,3,26,6,15,7,18,1,26,6,15,6,25,6,26,6,15,7,2,6,26,6,15,12,21,2,26,6,15,11,16,2,26,6,15,12,19,7,26,6,15,2,24,3,26,6,15,11,15,2,26,6,15,3,22,2,26,6,15,4,8,4,26,6,15,11,23,1,26,6,15,12,29,3,26,6,15,9,16,3,26,6,15,6,11,4,26,6,15,2,10,3,26,6,15,7,27,1,26,6,15,10,23,6,26,6,15,1,21,5,26,6,15,12,19,1,26,6,15,4,22,5,26,6,15,2,1,1,26,6,15,10,21,3,26,6,15,10,16,6,26,6,15,2,12,6,26,6,15,12,8,2,26,6,15,6,5,6,26,6,15,4,8,5,26,6,15,4,15,4,26,6,15,8,3,1,26,6,15,10,31,7,26,6,15,10,21,5,26,6,15,6,11,5,26,6,15,7,11,1,26,6,15,2,18,4,26,6,15,10,14,5,26,6,15,11,25,4,26,6,15,1,27,3,26,6,15,9,21,1,26,6,15,6,22,1,26,6,15,9,27,7,26,6,15,4,14,4,26,6,15,5,23,1,26,6,15,8,5,3,26,6,15,10,28,4,26,6,15,12,20,1,26,6,15,9,19,1,26,6,15,3,8,1,26,6,15,5,29,6,26,6,15,3,11,5,26,6,15,8,16,2,26,6,15,6,24,3,26,6,15,9,22,3,26,6,15,9,4,6,26,6,15,2,27,7,26,6,15,10,12,3,26,6,15,5,20,3,26,6,15,8,26,5,26,6,15,8,8,1,26,6,15,12,23,3,26,6,15,7,17,7,26,6,15,12,22,2,26,6,15,9,26,6,26,6,15,8,24,1,26,6,15,7,13,2,26,6,15,9,29,2,26,6,15,7,19,2,26,6,15,5,31,7,26,6,15,10,22,6,26,6,15,11,8,7,26,6,15,8,5,5,26,6,15,5,18,3,26,6,15,5,11,1,26,6,15,9,28,1,26,6,15,7,30,6,26,6,15,5,18,2,26,6,15,6,3,4,26,6,15,7,5,2,26,6,15,2,5,6,26,6,15,7,15,3,26,6,15,4,29,5,26,6,15,2,6,6,26,6,15,11,15,1,26,6,15,11,16,3,26,6,15,9,18,7,26,6,15,3,18,5,26,6,15,4,5,2,26,6,15,10,13,3,26,6,15,9,20,2,26,6,15,11,21,6,26,6,15,3,6,7,26,6,15,1,28,4,26,6,15,9,10,4,26,6,15,11,30,1,26,6,15,10,18,7,26,6,15,7,16,4,26,6,15,12,21,1,26,6,15,3,9,2,26,6,15,5,26,4,26,6,15,12,1,2,26,6,15,6,17,4,26,6,15,2,19,6,26,6,15,10,3,6,26,6,15,7,2,5,26,6,15,1,23,7,26,6,15,10,20,4,26,6,15,7,3,6,26,6,15,7,28,4,26,6,15,4,18,7,26,6,15,7,24,7,26,6,15,5,19,4,26,6,15,7,22,4,26,6,15,7,30,5,26,6,15,3,16,2,26,6,15,8,4,4,26,6,15,1,7,4,26,6,15,4,10,7,26,6,15,5,9,6,26,6,15,8,29,6,26,6,15,5,19,2,26,6,15,8,15,1,26,6,15,4,7,4,26,6,15,2,3,4,26,6,15,2,2,3,26,6,15,12,2,3,26,6,15,9,12,6,26,6,15,5,5,2,26,6,15,5,20,4,26,6,15,7,16,6,26,6,15,1,14,4,26,6,15,11,25,3,26,6,15,9,19,7,26,6,15,3,9,3,26,6,15,7,6,1,26,6,15,6,6,6,26,6,15,2,25,5,26,6,15,3,19,5,26,6,15,10,4,7,26,6,15,1,18,2,26,6,15,2,16,3,26,6,15,1,26,3,26,6,15,8,6,5,26,6,15,11,18,3,26,6,15,8,27,4,26,6,15,1,2,6,26,6,15,6,16,4,26,6,15,6,28,2,26,6,15,9,14,1,26,6,15,8,6,4,26,6,15,8,25,2,26,6,15,12,20,2,26,6,15,7,29,5,26,6,15,6,12,7,26,6,15,1,26,2,26,6,15,10,10,7,26,6,15,12,12,7,26,6,15,3,31,4,26,6,15,11,24,2,26,6,15,3,23,3,26,6,15,12,11,6,26,6,15,7,25,7,26,6,15,7,10,5,26,6,15,6,4,6,26,6,15,11,15,7,26,6,15,12,9,4,26,6,15,8,12,3,26,6,15,4,12,1,26,6,15,8,27,6,26,6,15,5,12,2,26,6,15,7,14,2,26,6,15,5,4,2,26,6,15,1,17,7,26,6,15,5,27,5,26,6,15,8,27,5,26,6,15,10,4,1,26,6,15,11,10,2,26,6,15,12,27,2,26,6,15,1,29,6,26,6,15,12,11,7,26,6,15,8,11,3,26,6,15,1,24,1,26,6,15,9,19,6,26,6,15,12,27,1,26,6,15,8,18,2,26,6,15,12,30,5,26,6,15,11,16,1,26,6,15,3,1,2,26,6,15,6,18,6,26,6,15,8,30,1,26,6,15,12,4,6,26,6,15,8,22,7,26,6,15,10,27,3,26,6,15,1,5,3,26,6,15,11,7,6,26,6,15,11,29,1,26,6,15,12,6,1,26,6,15,10,18,2,26,6,15,8,28,5,26,6,15,11,29,2,26,6,15,2,11,4,26,6,15,8,1,6,26,6,15,5,27,3,26,6,15,10,17,7,26,6,15,11,12,5,26,6,15,4,17,7,26,6,15,10,17,1,26,6,15,7,23,6,26,6,15,12,24,6,26,6,15,7,21,2,26,6,15,6,29,2,26,6,15,6,10,3,26,6,15,10,12,1,26,6,15,6,13,1,26,6,15,8,21,6,26,6,15,10,10,6,26,6,15,9,3,5,26,6,15,7,21,3,26,6,15,9,2,4,26,6,15,12,16,4,26,6,15,5,22,6,26,6,15,8,14,5,26,6,15,9,1,4,26,6,15,10,16,5,26,6,15,5,15,5,26,6,15,4,16,6,26,6,15,11,20,6,26,6,15,10,3,7,26,6,15,4,20,2,26,6,15,11,24,4,26,6,15,10,30,7,26,6,15,12,22,3,26,6,15,4,21,3,26,6,15,11,28,7,26,6,15,9,22,4,26,6,15,4,1,5,26,6,15,11,9,1,26,6,15,11,18,4,26,6,15,3,20,6,26,6,15,6,21,7,26,6,15,12,22,4,26,6,15,6,13,6,26,6,15,7,18,7,26,6,15,10,19,1,26,6,15,7,30,4,26,6,15,9,21,3,26,6,15,11,1,2,26,6,15,6,11,6,26,6,15,8,26,3,26,6,15,2,17,3,26,6,15,8,20,6,26,6,15,4,21,4,26,6,15,8,11,2,26,6,15,6,30,4,26,6,15,2,20,6,26,6,15,10,5,3,26,6,15,3,12,6,26,6,15,3,3,3,26,6,15,6,9,2,26,6,15,4,30,6,26,6,15,10,25,7,26,6,15,10,6,2,26,6,15,10,29,6,26,6,15,7,9,4,26,6,15,7,13,1,26,6,15,1,3,1,26,6,15,3,13,6,26,6,15,5,15,6,26,6,15,11,4,3,26,6,15,12,3,5,26,6,15,5,29,7,26,6,15,11,14,6,26,6,15,8,17,2,26,6,15,12,17,5,26,6,15,6,16,2,26,6,15,6,10,5,26,6,15,6,27,7,26,6,15,10,23,7,26,6,15,5,24,2,26,6,15,11,3,2,26,6,15,12,29,2,26,6,15,11,17,3,26,6,15,4,3,6,26,6,15,1,22,5,26,6,15,2,2,2,26,6,15,2,13,6,26,6,15,4,5,1,26,6,15,6,4,4,26,6,15,5,13,5,26,6,15,1,28,5,26,6,15,2,26,5,26,6,15,6,20,6,26,6,15,3,17,3,26,6,15,11,3,4,26,6,15,12,9,5,26,6,15,10,1,6,26,6,15,8,31,1,26,6,15,6,15,3,26,6,15,8,31,3,26,6,15,10,16,7,26,6,15,7,7,4,26,6,15,6,3,5,26,6,15,12,23,5,26,6,15,4,26,2,26,6,15,5,16,1,26,6,15,6,3,3,26,6,15,11,30,3,26,6,15,11,8,2,26,6,15,12,11,5,26,6,15,10,15,4,26,6,15,12,2,4,26,6,15,6,7,1,26,6,15,4,6,3,26,6,15,3,30,3,26,6,15,11,19,6,26,6,15,8,14,6,26,6,15,12,28,3,26,6,15,4,17,6,26,6,15,8,2,7,26,6,15,10,28,5,26,6,15,8,29,1,26,6,15,7,1,5,26,6,15,12,29,4,26,6,15,10,24,1,26,6,15,7,12,7,26,6,15,12,30,3,26,6,15,8,25,3,26,6,15,6,12,6,26,6,15,9,29,3,26,6,15,8,4,3,26,6,15,8,13,4,26,6,15,11,13,5,26,6,15,8,20,5,26,6,15,5,31,2,26,6,15,11,5,5,26,6,15,7,22,3,26,6,15,10,14,4,26,6,15,6,22,2,26,6,15,7,20,3,26,6,15,2,24,4,26,6,15,7,26,1,26,6,15,6,28,7,26,6,15,12,9,3,26,6,15,3,26,6,26,6,15,11,30,2,26,6,15,9,13,7,26,6,15,8,24,3,26,6,15,12,31,5,26,6,15,4,6,2,26,6,15,9,11,6,26,6,15,4,27,2,26,6,15,1,21,4,26,6,15,7,17,6,26,6,15,11,19,4,26,6,15,11,18,5,26,6,15,2,22,1,26,6,15,6,26,6,26,6,15,4,28,3,26,6,15,9,17,4,26,6,15,9,9,3,26,6,15,12,10,6,26,6,15,10,11,7,26,6,15,4,28,4,26,6,15,7,18,6,26,6,15,1,22,6,26,6,15,5,10,7,26,6,15,9,29,4,26,6,15,11,2,3,26,6,15,7,6,3,26,6,15,3,5,5,26,6,15,7,8,5,26,6,15,8,19,4,26,6,15,7,8,4,26,6,15,11,17,2,26,6,15,7,24,6,26,6,15,11,8,1,26,6,15,7,25,6,26,6,15,11,22,2,26,6,15,12,18,5,26,6,15,5,12,4,26,6,15,7,22,5,26,6,15,8,22,6,26,6,15,8,24,2,26,6,15,11,1,7,26,6,15,4,25,7,26,6,15,5,11,3,26,6,15,8,12,5,26,6,15,10,23,5,26,6,15,10,9,5,26,6,15,1,15,5,26,6,15,8,14,7,26,6,15,1,11,2,26,6,15,4,14,3,26,6,15,6,22,3,26,6,15,1,25,2,26,6,15,7,4,1,26,6,15,11,23,2,26,6,15,8,2,2,26,6,15,1,19,2,26,6,15,8,23,1,26,6,15,1,25,1,26,6,15,9,17,6,26,6,15,12,8,4,26,6,15,11,6,7,26,6,15,6,23,4,26,6,15,3,15,1,26,6,15,7,1,4,26,6,15,1,3,7,26,6,15,12,3,6,26,6,15,4,27,3,26,6,15,11,17,4,26,6,15,11,12,4,26,6,15,3,31,3,26,6,15,6,25,4,26,6,15,12,4,5,26,6,15,9,2,3,26,6,15,9,6,7,26,6,15,5,21,6,26,6,15,8,4,2,26,6,15,9,4,5,26,6,15,3,23,2,26,6,15,2,9,2,26,6,15,10,1,5,26,6,15,4,29,4,26,6,15,5,30,7,26,6,15,1,20,3,26),
nrow=625, ncol=6, byrow=TRUE);

y <-
factor(c(4.0,1.0,1.0,2.0,1.0,3.0,1.0,1.0,3.0,3.0,1.0,7.0,1.0,12.0,4.0,2.0,7.0,1.0,12.0,7.0,5.0,1.0,12.0,6.0,15.0,1.0,7.0,3.0,3.0,9.0,1.0,1.0,3.0,2.0,1.0,2.0,2.0,1.0,9.0,1.0,1.0,1.0,4.0,4.0,1.0,1.0,1.0,5.0,2.0,1.0,2.0,2.0,1.0,1.0,7.0,2.0,3.0,2.0,4.0,3.0,1.0,1.0,2.0,2.0,1.0,9.0,2.0,1.0,2.0,1.0,1.0,5.0,7.0,4.0,4.0,1.0,2.0,2.0,1.0,7.0,1.0,8.0,3.0,14.0,6.0,5.0,3.0,5.0,2.0,1.0,3.0,7.0,17.0,2.0,2.0,8.0,2.0,6.0,1.0,6.0,11.0,2.0,10.0,2.0,1.0,5.0,4.0,1.0,5.0,2.0,24.0,3.0,4.0,11.0,12.0,1.0,2.0,1.0,4.0,17.0,2.0,2.0,2.0,5.0,1.0,2.0,2.0,1.0,3.0,2.0,4.0,1.0,3.0,3.0,5.0,7.0,4.0,1.0,4.0,1.0,2.0,5.0,1.0,11.0,1.0,2.0,1.0,1.0,12.0,5.0,1.0,13.0,7.0,1.0,1.0,4.0,2.0,12.0,7.0,1.0,4.0,1.0,1.0,7.0,1.0,5.0,1.0,6.0,4.0,4.0,1.0,3.0,2.0,5.0,10.0,1.0,3.0,2.0,2.0,4.0,4.0,14.0,1.0,4.0,1.0,1.0,4.0,4.0,7.0,2.0,2.0,4.0,2.0,2.0,12.0,1.0,3.0,6.0,3.0,3.0,1.0,2.0,1.0,1.0,4.0,3.0,3.0,5.0,1.0,1.0,2.0,1.0,2.0,3.0,3.0,10.0,1.0,1.0,2.0,1.0,1.0,2.0,3.0,3.0,2.0,3.0,3.0,8.0,1.0,1.0,2.0,6.0,5.0,2.0,1.0,7.0,4.0,1.0,10.0,1.0,2.0,6.0,1.0,1.0,4.0,2.0,7.0,10.0,2.0,2.0,1.0,1.0,2.0,1.0,11.0,30.0,3.0,13.0,3.0,1.0,15.0,3.0,2.0,4.0,1.0,7.0,4.0,1.0,1.0,2.0,18.0,2.0,3.0,1.0,1.0,3.0,3.0,4.0,3.0,12.0,3.0,6.0,2.0,11.0,5.0,1.0,7.0,2.0,15.0,7.0,1.0,1.0,18.0,3.0,1.0,1.0,2.0,3.0,1.0,2.0,2.0,2.0,3.0,10.0,2.0,4.0,6.0,7.0,8.0,3.0,5.0,2.0,7.0,2.0,2.0,1.0,1.0,1.0,4.0,1.0,5.0,8.0,5.0,1.0,10.0,4.0,1.0,7.0,1.0,2.0,3.0,3.0,6.0,1.0,5.0,2.0,1.0,2.0,4.0,1.0,1.0,2.0,1.0,1.0,1.0,5.0,5.0,2.0,17.0,2.0,3.0,2.0,1.0,2.0,3.0,4.0,9.0,2.0,1.0,1.0,2.0,1.0,9.0,6.0,7.0,1.0,14.0,3.0,1.0,1.0,12.0,2.0,13.0,4.0,2.0,2.0,1.0,1.0,1.0,8.0,1.0,2.0,1.0,3.0,1.0,4.0,4.0,10.0,4.0,11.0,1.0,1.0,2.0,6.0,2.0,2.0,1.0,1.0,7.0,11.0,3.0,3.0,3.0,5.0,2.0,1.0,2.0,24.0,6.0,5.0,6.0,4.0,1.0,3.0,5.0,2.0,3.0,2.0,5.0,3.0,2.0,6.0,3.0,5.0,7.0,7.0,6.0,6.0,1.0,1.0,12.0,2.0,10.0,4.0,1.0,1.0,1.0,1.0,1.0,7.0,7.0,8.0,2.0,1.0,1.0,12.0,8.0,1.0,1.0,2.0,3.0,15.0,1.0,1.0,1.0,4.0,1.0,1.0,2.0,6.0,1.0,8.0,1.0,5.0,3.0,14.0,2.0,6.0,7.0,1.0,3.0,2.0,3.0,1.0,1.0,2.0,4.0,4.0,2.0,1.0,1.0,1.0,11.0,1.0,3.0,9.0,1.0,14.0,2.0,1.0,1.0,1.0,6.0,2.0,5.0,2.0,1.0,4.0,1.0,3.0,2.0,3.0,6.0,6.0,1.0,8.0,5.0,2.0,6.0,3.0,1.0,1.0,1.0,1.0,14.0,1.0,7.0,12.0,3.0,9.0,8.0,1.0,5.0,2.0,3.0,1.0,2.0,2.0,13.0,3.0,1.0,5.0,8.0,1.0,5.0,3.0,7.0,1.0,1.0,2.0,1.0,6.0,2.0,2.0,7.0,5.0,1.0,3.0,1.0,2.0,1.0,1.0,2.0,3.0,1.0,9.0,5.0,14.0,2.0,4.0,5.0,3.0,2.0,10.0,14.0,5.0,3.0,1.0,1.0,3.0,2.0,2.0,2.0,2.0,2.0,4.0,10.0,10.0,1.0,5.0,1.0,1.0,4.0,6.0,1.0,13.0,3.0,3.0,2.0,1.0,1.0,4.0,1.0,1.0,1.0,5.0,3.0,1.0,5.0,2.0,2.0,3.0,12.0,8.0,2.0,1.0,6.0,3.0,1.0,1.0,1.0,2.0,4.0,2.0,9.0,2.0,3.0,2.0,9.0,2.0,2.0,7.0,20.0,1.0,2.0));

z <-
matrix(data=c(6,15,1,1,7,26,6,15,1,2,1,26,6,15,1,3,2,26,6,15,1,4,3,26,6,15,1,5,4,26,6,15,1,6,5,26,6,15,1,7,6,26,6,15,1,8,7,26,6,15,1,9,1,26,6,15,1,10,2,26,6,15,1,11,3,26,6,15,1,12,4,26,6,15,1,13,5,26,6,15,1,14,6,26,6,15,1,15,7,26,6,15,1,16,1,26,6,15,1,17,2,26,6,15,1,18,3,26,6,15,1,19,4,26,6,15,1,20,5,26,6,15,1,21,6,26,6,15,1,22,7,26,6,15,1,23,1,26,6,15,1,24,2,26,6,15,1,25,3,26,6,15,1,26,4,26,6,15,1,27,5,26,6,15,1,28,6,26,6,15,1,29,7,26,6,15,1,30,1,26,6,15,1,31,2,26,6,15,2,1,3,26,6,15,2,2,4,26,6,15,2,3,5,26,6,15,2,4,6,26,6,15,2,5,7,26,6,15,2,6,1,26,6,15,2,7,2,26,6,15,2,8,3,26,6,15,2,9,4,26,6,15,2,10,5,26,6,15,2,11,6,26,6,15,2,12,7,26,6,15,2,13,1,26,6,15,2,14,2,26,6,15,2,15,3,26,6,15,2,16,4,26,6,15,2,17,5,26,6,15,2,18,6,26,6,15,2,19,7,26,6,15,2,20,1,26,6,15,2,21,2,26,6,15,2,22,3,26,6,15,2,23,4,26,6,15,2,24,5,26,6,15,2,25,6,26,6,15,2,26,7,26,6,15,2,27,1,26,6,15,2,28,2,26,6,15,2,29,3,26,6,15,3,1,4,26,6,15,3,2,5,26,6,15,3,3,6,26,6,15,3,4,7,26,6,15,3,5,1,26,6,15,3,6,2,26,6,15,3,7,3,26,6,15,3,8,4,26,6,15,3,9,5,26,6,15,3,10,6,26,6,15,3,11,7,26,6,15,3,12,1,26,6,15,3,13,2,26,6,15,3,14,3,26,6,15,3,15,4,26,6,15,3,16,5,26,6,15,3,17,6,26,6,15,3,18,7,26,6,15,3,19,1,26,6,15,3,20,2,26,6,15,3,21,3,26,6,15,3,22,4,26,6,15,3,23,5,26,6,15,3,24,6,26,6,15,3,25,7,26,6,15,3,26,1,26,6,15,3,27,2,26,6,15,3,28,3,26,6,15,3,29,4,26,6,15,3,30,5,26,6,15,3,31,6,26),
nrow=91, ncol=6, byrow=TRUE);

model <- randomForest (x, y);

t <- factor (predict(model, z, type='response', predict.all=FALSE));

..............

--
Anthony

--
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