Makes predictions using a random regression forest (R.W. Payne).
Options
PRINT = string token |
Controls printed output (prediction ); default pred |
---|---|
PREDICTION = variate |
Saves the prediction for the observations |
SAVE = pointer |
Save structure from BRFOREST providing information about the random forest |
Parameters
X = variates or factors |
Explanatory variables |
---|---|
VALUES = scalars, variates or texts |
Values to use for the explanatory variables; if these are unset for any variable, its existing values are used |
Description
BRFPREDICT
makes predictions using a regression forest, as constructed by the BRFOREST
procedure. The SAVE
parameter can be set to a pointer, saved using the SAVE
option of BRFOREST
, containing the necessary information about the forest. Alternatively, if you do not set SAVE
, BRFPREDICT
will use the forest most recently constructed by BRFOREST
.
The x-values for the predictions can be specified in the variates listed by the X
parameter. These must have identical names (and levels) to those used originally to construct the tree. You can use the VALUES
parameter to supply new values, if those stored in any of the variates or factors are unsuitable.
By default, BRFPREDICT
prints the predictions, but you can set option PRINT=*
to suppress this. The PREDICTION
option allows you to save the predictions.
Options: PRINT
, PREDICTION
, SAVE
.
Parameters: X
, VALUES
.
Method
BRFPREDICT
takes the mean of predictions from the individual trees, made using BIDENTIFY
.
Action with RESTRICT
Restrictions are ignored.
See also
Procedures: BRFOREST
, BRFDISPLAY
, BREGRESSION
, BRPREDICT
.
Commands for: Regression analysis, Multivariate and cluster analysis.
Example
CAPTION 'BRFPREDICT example'; STYLE=meta SPLOAD [PRINT=*] '%gendir%/data/water.gsh' BRFOREST [PRINT=outofbagerror,youtofbagestimates,importance;\ Y=Water; NTREES=8; NXTRY=3; NUNITSTRY=10; SEED=185090]\ Employ,Opdays,Product,Temp BRFPREDICT [PREDICTION=prediction] Opdays,Product,Temp;\ VALUES=!(20,23,20),!(11.96,13.53,12.66),!(71.90,63.90,54.50)