The arboretum procedure



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The NEURAL Procedure

DELETE_Statement__If_an_input_or_hidden_layer_is_not_contributing_the_predictive_ability_of_the_network,_you_can'>DELETE Statement

If an input or hidden layer is not contributing the predictive ability of the network, you can

remove that layer with a DELETE statement. The DELETE statement also removes all associated

weights.

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

affect only that statement.



DELETE id-list;

Required Argument

id-list

Specifies the identifiers of layers to delete.

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



The NEURAL Procedure

FREEZE Statement

Normally during training, all weights are updated. If you freeze one or more weights, those

weights will retain their frozen value until a corresponding THAW statement is executed. Freezing

weights causes training to proceed faster and require less memory.

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

affect only that statement.



FREEZE weight-list / <VALUE=number>

<EST=SAS-data-set>;

Required Argument

weight-list

List of weights to freeze.

Weight-list consists of 0 or more repetitions of:

wname --> wname-2 where:

wname

is a unit name, a layer identifier, BIAS, or ALTITUDE



wname-2

is a unit name or a layer identifier



Options

You can specify either VALUE= or EST= but not both. If neither option is specified, the weights are

frozen to their current values.

VALUE=number

Specifies the numeric value to which weights are to be frozen.



EST=SAS-data-set

Specifies the SAS data set containing the values to which weights are to be frozen.

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



The NEURAL Procedure

FREQ Statement

Specifies the frequency variable for training.

Category Variable Statement - specifies variables.

FREQ variable;

Options

variable

Specifies the frequency variable. (The frequency variable can contain integer and non-integer

values.)

Note:   The FREQ variable is not required in the DATA= data set. The NEURAL procedure

searches for the name of the FREQ variable in the DATA=, VALIDATA=, and TESTDATA=

data sets. If the FREQ variable does not appear in any of these data sets, then the procedure issues

a warning but continues processing. For any data set that does not contain the FREQ variable, a

FREQ value of 1 is used for all observations.  

Default:

The default value is taken from the DMDB metadata. The FREQ statement

overrides whatever is in the DMDB metadata. If a FREQ statement contains

no variable name, then no FREQ variable is used.

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



The NEURAL Procedure

HIDDEN Statement

You can specify as many HIDDEN statements as you want up to the limits imposed by computer

memory, time, and disk space. The hidden layers can be connected in any feedforward pattern

using CONNECT statements.

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

affect only that statement.



HIDDEN integer / ID=name

<ACT=activation-function>

<BIAS|NOBIAS>

<COMBINE=combination-function>;

Required Arguments

integer

Specifies the number of units in the hidden layer.



ID=name

Specifies the identifier for the layer.



Options

ACT=activation-function

Specifies the activation function. See 

ACTIVATION FUNCTIONS

.

Default:

For hidden units, the default activation function depends on the combination

function and on the number of units in the layer.

For COMBINE=ADD, the default is ACT=IDENTITY.

For COMBINE=LINEAR or EQSLOPES, the default is ACT=TANH.

For COMBINE=EHRADIAL, EQRADIAL, EVRADIAL,

EWRADIAL, or XRADIAL, the default is ACT=EXP if there is only

one hidden unit in the layer; otherwise the default is ACT=SOFTMAX.

BIAS | NOBIAS

Specifies whether to use bias.




Default:

BIAS


COMBINE=combination-function

Specifies the combination function. See 

COMBINATION FUNCTIONS

.

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




The NEURAL Procedure

ACTIVATION FUNCTIONS

Activation Functions

FUNCTION

RANGE

FUNCTION

(OF NET INPUT t)

IDEntity


LINear

EXPonential

RECiprocal

SQUare


LOGistic

MLOgistic

SOFtmax

GAUss


SINe

COSine


ELLiott

TANh





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