The arboretum procedure



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The NEURAL Procedure

QUIT Statement

Stops the procedure.

Category Action Statement - affects the network or the data sets. Options'>Options set in an action statement

affect only that statement.



QUIT;

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.




The NEURAL Procedure

RANOPTIONS_Statement__Specifies_distribution_of_random_initial_weights.__Category'>RANOPTIONS Statement

Specifies distribution of random initial weights.

Category Option Statement - does not directly affect the network, but sets options for use in

subsequent action statements. The options persist until reset at a later stage in the

processing.

RANOPTIONS connection-list /

<RANDF=number>

<RANDIST=name>

<RANDOM=integer>

<RANLOC=number>

<RANSCALE=number>;

Required Arguments

Note:   When a RANOPTIONS statement is executed, the specified options are stored in all the

connections listed before the slash. These options are used whenever an INITIAL or PRELIM statement

is executed. If you submit two RANOPTIONS statements for the same connection, the second statement

overrides all options in the first. In other words, one RANOPTIONS statement does not remember what

options were specified in previous RANOPTIONS statements. To have options persist over multiple

statements, use the NETOPTIONS statement.  



connection-list

List of connections to randomize.



connection-list consists of 0 or more repetitions of:

wname --> wname-2 where:

wname

is the layer ID, BIAS, or ALTITUDE



wname-2

is the layer ID



Options

RANDF=number

Specifies the degrees of freedom parameter for random numbers. See the 

Randomization Options



and Default Parameters

 table for values.



Default:

1

RANDIST=name

Specifies the type of distribution for random numbers. See the 

Randomization Options and

Default Parameters

 table for values.



Default:

NORMAL


RANDOM=integer

Specifies the random number seed.



Default:

0

RANLOC=number

Specifies the location parameter for random numbers. See the 

Randomization Options and Default

Parameters

 table for values.



RANSCALE=number

Specifies the scale parameter for random numbers. See the 

Randomization Options and Default

Parameters

 table for values.

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.




The NEURAL Procedure

SAVE Statement

Writes weights to data set or a description of the network to a catalog entry.

Category Action Statement - affects the network or the data sets. Options set in an action statement

affect only that statement.



NOTE: At least one option must be specified, but there is no single argument that is required.

SAVE OUTEST=SAS-data-set

NETWORK=screen-specification;

Options

Specify at least one:



NETWORK=screen-specification

Saves the definition of the entire network. screen-specification is the name of a catalog entry.



OUTEST= SAS-data-set

Saves the network weights in an output data set.

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.



The NEURAL Procedure

SCORE Statement

Creates an output data set containing predicted values and possibly other results such as residuals,

classifications, decisions, and assessment values.

Category Action Statement - affects the network or the data sets. Options set in an action statement

affect only that statement.



SCORE DATA=SAS-data-set

OUT=SAS-data-set

OUTFIT=SAS-data-set

<DUMMIES | NODUMMIES>

<ROLE=role-option>;

Required Arguments

OUT=SAS-data-set

Specifies the output data set that contains the outputs.



Options

DATA=SAS-data-set

Specifies the input data to be scored that contains inputs and, optionally, targets.



Default:

Defaults to the training data (DATA= in the PROC statement).



DUMMIES | NODUMMIES

Specifies whether to write dummy variables to the OUT= data set.



Default:

NODUMMIES



OUTFIT=SAS-data-set

Specifies the output data set that contains the fit statistics.



ROLE=role-option

Specifies the role of the DATA= data set. ROLE=role-option primarily affects which fit statistics

are computed and what their names and labels are. Role-option is one of the following:

TRAIN


Specifies that the DATA= data set is the training set. The data set must contain the target

variable.






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