Get Quantile Cuts from DMatrix

Get the quantile cuts (a.k.a. borders) from an xgb.DMatrix that has been quantized for the histogram method (tree_method = "hist").

These cuts are used in order to assign observations to bins - i.e. these are ordered boundaries which are used to determine assignment condition border_low < x < border_high. As such, the first and last bin will be outside of the range of the data, so as to include all of the observations there.

If a given column has 'n' bins, then there will be 'n+1' cuts / borders for that column, which will be output in sorted order from lowest to highest.

Different columns can have different numbers of bins according to their range.

Usage

xgb.get.DMatrix.qcut(dmat, output = c("list", "arrays"))

Arguments

dmat

An xgb.DMatrix object, as returned by xgb.DMatrix().

output

Output format for the quantile cuts. Possible options are:

• "list"will return the output as a list with one entry per column, where each column will have a numeric vector with the cuts. The list will be named ifdmat` has column names assigned to it.

• "arrays" will return a list with entries indptr (base-0 indexing) and data. Here, the cuts for column 'i' are obtained by slicing 'data' from entries indptr[i]+1 to indptr[i+1].

Value

The quantile cuts, in the format specified by parameter output.

Examples

data(mtcars)

y <- mtcars$mpg
x <- as.matrix(mtcars[, -1])
dm <- xgb.DMatrix(x, label = y, nthread = 1)

# DMatrix is not quantized right away, but will be once a hist model is generated
model <- xgb.train(
  data = dm,
  params = xgb.params(tree_method = "hist", max_bin = 8, nthread = 1),
  nrounds = 3
)

# Now can get the quantile cuts
xgb.get.DMatrix.qcut(dm)
#> $cyl
#> [1] -0.00001  6.00000  8.00000 16.00001
#> 
#> $disp
#> [1]  -0.00001  95.10000 121.00000 160.00000 225.00000 275.79999 318.00000
#> [8] 360.00000 944.00000
#> 
#> $hp
#> [1]  -0.00001  66.00000  97.00000 110.00000 123.00000 175.00000 180.00000
#> [8] 230.00000 670.00000
#> 
#> $drat
#> [1] -0.000010  3.070000  3.150000  3.230000  3.700000  3.900000  3.920000
#> [8]  4.110000  9.860009
#> 
#> $wt
#> [1] -0.00001  2.14000  2.62000  3.15000  3.43500  3.44000  3.57000  3.84500
#> [9] 10.84801
#> 
#> $qsec
#> [1] -0.00001 15.84000 16.90000 17.30000 17.82000 18.30000 18.90000 19.90000
#> [9] 45.80001
#> 
#> $vs
#> [1] -0.00001  1.00000  2.00001
#> 
#> $am
#> [1] -0.00001  1.00000  2.00001
#> 
#> $gear
#> [1] -0.00001  4.00000  5.00000 10.00001
#> 
#> $carb
#> [1] -0.00001  2.00000  3.00000  4.00000  6.00000  8.00000 16.00001
#>