Out-of-bag regression error
L = oobLoss(ens)
L = oobLoss(ens,Name,Value)
returns
the mean squared error for L
= oobLoss(ens
)ens
computed for out-of-bag
data.
computes
error with additional options specified by one or more L
= oobLoss(ens
,Name,Value
)Name,Value
pair
arguments. You can specify several name-value pair arguments in any
order as Name1,Value1,…,NameN,ValueN
.
|
A regression bagged ensemble, constructed with |
Specify optional
comma-separated pairs of Name,Value
arguments. Name
is
the argument name and Value
is the corresponding value.
Name
must appear inside quotes. You can specify several name and value
pair arguments in any order as
Name1,Value1,...,NameN,ValueN
.
|
Indices of weak learners in the ensemble ranging from Default: |
|
Function handle for loss function, or FUN(Y,Yfit,W) where Default: |
|
Character vector or string scalar representing the meaning of the output
Default: |
|
Mean squared error of the out-of-bag observations, a scalar. |