earth
objectevimp(obj, trim=TRUE, sqrt.=FALSE)
earth
object.sqrt
of the GCV and RSS importances before
normalizing to 0 to 100.
This arguably gives a better indication of relative importances
because the raw importanc-unused
appended if the
variable does not appear in the final model.The columns of the matrix are:
col
: column index of the variable in the x
argument to earth
.
used
: 1 if the variable is used in the final model, else 0.
Equivalently, 0 if the row name has a -unused
suffix.
nsubsets
: variable importance using the "number of subsets" criterion.
Is the number of subsets that include the variable (see "Three Criteria" below).
gcv
: variable importance using the GCV criterion (see below).
rss
: variable importance using the RSS criterion (see below).
The rows are sorted on the nsubsets
criterion.
This means that values in the nsubsets
column decrease as you go down the column
(more accurately, they are non-increasing).
The values in the gcv
and rss
columns
are also non-increasing, except where the
gcv
or rss
ranking differs from the nsubsets
ranking.
For convenience scanning the columns by eye, there are unnamed columns (not listed above)
after the gcv
column and the rss
column.
These have a 0 where the ranking using the gcv
or rss
criteria differs from
that using the nsubsets
criterion.
In other words, there is a 0 for values that increase as you go
down the gcv
or rss
column.
earth
,
plot.evimp
data(ozone1)
a <- earth(O3 ~ ., data=ozone1, degree=2)
ev <- evimp(a, trim=FALSE, sqrt.=TRUE)
plot(ev)
print(ev)
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