tree in the
Specifies that no node is split on an input an ancestor is split on.
Names the input SAS data set for validation.
Specifies a threshold p-value for the worth of a candidate splitting rules. The measure of worth
depends on the CRITERION= method.
For a method based on p-values, the threshold is a maximum acceptable
the measure of worth.
For a method based on p-values, the default is 0.20; for other criteria, the
default is 0.
Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
Requests creation of a dummy variable for each leaf node. The value of the dummy variable is 1
for observations in the leaf and 0 for all other observations.
Specifies the file name that contains the code.
Specifies the format to be used in the DATA step code for numeric values that don't have a format
from the input data set.
Suppresses the creation of the _NODE_ variable containing a numeric id of the leaf to which the
observation is assigned.
Suppresses the creation of predicted variables, such as P_*.
Requests code that assumes the existence of the target variable.
By default, the code contains no reference to the target variable (to avoid
confusing notes or warnings). The code computes values that depend on the
target variable (such as the R_*, E_*, F_*, CL_*, CP_*, BL_*, BP_*, or
ROI_* variables) only if the RESIDUAL option is specified.
for the DMREG and SPLIT procedures.
Specifies the input data set that contains the decision matrix. The DECDATA= data set must
contain the target variable.
Note: The DECDATA= data set may also contain decision variables specified by means of the
DECVARS= option, and prior probability variable(s) specified by means of the PRIORVAR=
option or the OLDPRIORVAR= option, or both.
The target variable is specified by means of the TARGET statement in the DECIDE, NEURAL,
and SPLIT procedures or the MODEL statement in the DMREG procedure. If the target variable
in the DATA= data set is categorical then the target variable of the DECDATA= data set should
contain the category values, and the decision variables will contain the common consequences of
making those decisions for the corresponding target level. If the target variable is interval, then
each decision variable will contain the value of the consequence for that decision at a point
specified in the target variable. The unspecified regions of the decision function are interpolated
by a piecewise linear spline.
The DECDATA= data set may be of TYPE=LOSS, PROFIT, or REVENUE.
If unspecified, TYPE= is assumed to be PROFIT by default. TYPE= is a data
set option that should be specified when the data set is created.
Specifies the decision variables in the DECDATA= data set that contain the target-specific
consequences for each decision.
Specifies numeric constants giving the cost of a decision, or variables in the DATA= data set that
contain the case-specific costs, or any combination of constants and variables. There must be the
same number of cost constants and variables as there are decision variables in the DECVARS=
ABC--XYZ, or PQR:.
All costs are assumed to be 0.
Specifies the variable in the DECDATA= data set that contains the prior probabilities to use for
making decisions. In the DECIDE procedure, if PRIORVAR= is specified, OLDPRIORVAR=
must also be specified.
Specifies the variable in the DECDATA= data set that contains the prior probabilities that were
used when originally fitting the model. If OLDPRIORVAR= is specified, PRIORVAR= must also
OLDPRIORVAR= is not allowed in PROC SPLIT.