Display a summary of the structure of a Xfgpm
object, with a short description of up to n fgpm
objects visited during the ACO optimization.
# S4 method for Xfgpm
summary(object, n = 24, ...)A Xfgpm object.
Maximal number of lines (fgpm objects) to show.
Not used yet.
An object inheriting from list, actually a list
containing one or two data frames depending on the number of
inputs. In each data frame, the n rows provide
information on the best fgpm objects visited.
The displayed information depends on the number of
candidate inputs, in order to maintain compact tables. The
inputs are labelled with integer suffixes, the prefix being
"X" for scalar inputs and "F" for functional
inputs.
With a small number of inputs, the list
contains only one data frame. For each candidate
input (either scalar or functional) a column with
the input name indicates if the input
is active (cross x) or not (white space)
in the fgpm object corresponding to the row. For each
functional variable also shown are: the distance used D_,
the dimension Bas_ after dimension reduction,
the type of basis used B_. Remind that the
kernel (Kern) is the same for all functional
inputs. Also shown is the value of the Leave-One-Out
coefficient Q².
With a large number of inputs, the list contains two data frames. The first one tells which inputs are active among the scalar and functional candidate inputs. The second data frame gives more details for functional inputs as before.
summary(xm)
#> Inputs and details
#> X1 X2 X3 X4 X5 F1 D_F1 Dim_F1 Bas_F1 F2 D_F2 Dim_F2 Bas_F2 Kern Q2
#> 1 x x x x x idx 1 Bspl x idx 3 Bspl gauss 0.939
#> 2 x x x x x idx 1 PCA x idx 3 Bspl gauss 0.854
#> 3 x x x x idx 1 Bspl x idx 3 Bspl gauss 0.854
#> 4 x x x x grp 1 Bspl x idx 3 Bspl gauss 0.854
#> 5 x x x x x idx 1 Bspl x idx 3 Bspl mat32 0.845
#> 6 x x x x -- - -- x idx 3 Bspl gauss 0.841
#> 7 x x x x idx 1 Bspl x idx 3 Bspl mat32 0.833
#> 8 x x x x idx 1 Bspl x idx 3 Bspl mat52 0.809
#> 9 x x x x idx 1 Bspl x grp 22 PCA gauss 0.788
#> 10 x x x x idx 1 PCA x idx 3 Bspl mat32 0.785
#> 11 x x x -- - -- x idx 3 Bspl mat32 0.753
#> 12 x x x x idx 1 Bspl x idx 3 PCA gauss 0.721
#> 13 x x x x x idx 1 Bspl x idx 1 Bspl gauss 0.678
#> 14 x x x -- - -- x idx 3 Bspl gauss 0.623
#> 15 x x x x idx 1 PCA x idx 3 PCA gauss 0.596
#> 16 x x -- - -- x idx 3 PCA gauss 0.589
#> 17 x x x idx 1 Bspl x idx 3 Bspl mat32 0.570
#> 18 x x x x x idx 1 Bspl x idx 3 PCA gauss 0.553
#> 19 x x x x grp 5 Bspl x idx 3 PCA mat32 0.487
#> 20 x x -- - -- x idx 3 Bspl mat32 0.477
#> 21 x x -- - -- x idx 3 Bspl mat52 0.469
#> 22 x x x x grp 2 PCA x idx 3 Bspl mat32 0.402
#> 23 x x -- - -- x idx 3 PCA mat32 0.379
#> 24 x x x x -- - -- x idx 3 Bspl mat32 0.098