predictorImportance
Estimates of predictor importance for regression ensemble
Syntax
imp = predictorImportance(ens)
[imp,ma]
= predictorImportance(ens)
Description
computes estimates of predictor importance for
imp
= predictorImportance(ens
)ens
by summing these estimates
over all weak learners in the ensemble.
imp
has one element for each
input predictor in the data used to train this
ensemble. A high value indicates that this
predictor is important for
ens
.
[
returns a
imp
,ma
]
= predictorImportance(ens
)P
byP
matrix with predictive measures of association for
P
predictors.
Input Arguments

A regression ensemble, created by 
Output Arguments

A row vector with the same number of
elements as the number of predictors (columns) in


A

Examples
More About
Algorithms
Element ma(i,j)
is the
predictive measure of association averaged over
surrogate splits on predictor j
for which predictor i
is the
optimal split predictor. This average is computed
by summing positive values of the predictive
measure of association over optimal splits on
predictor i
and surrogate
splits on predictor j
and
dividing by the total number of optimal splits on
predictor i
, including splits
for which the predictive measure of association
between predictors i
and
j
is negative.