The arboretum procedure



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The NEURAL Procedure

PERTURB_Statement__Perturbs_weights._Perturbing_weights_can_sometimes_allow_you_to_escape_a_local_minimum.__Category'>PERTURB Statement

Perturbs weights. Perturbing weights can sometimes allow you to escape a local minimum.

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

affect only that statement.



PERTURB weight-list / <RANDF=number >

<OUTEST=SAS-data-set>

<RANDIST=name>

<RANDOM=integer>

<RANLOC=number>

<RANSCALE=number>;

Required Argument

weight-list

List of weights to freeze.

Weight-list consists of 0 or more repetitions of:

wname --> wname-2 where:

wname

is the unit name, the layer ID, BIAS, or ALTITUDE



wname-2

is the unit name or layer ID



Options

RANDF=number

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

Randomization Options

and Default Parameters

 table for values.

OUTEST=SAS-data-set

Specifies the output data set containing all the weights.



Default:

none


RANDIST=name


Specifies the type of distribution for random numbers. See the 

Randomization Options and

Default Parameters

 table for values.



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

PRELIM Statement

Performs preliminary training to reduce the risk of bad local optima.The final weights and biases

in a trained network depend on the initial values. The PRELIM statement repeatedely trains a

network for a smal number of iterations (default 20) using different initializations. The final

weights of the best trained network are then used to initialize a subsequent TRAIN statement.

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

affect only that statement.



PRELIM integer

<ACCELERATE=number>

<DECELERATE=number>

<INEST=SAS-data-set>

<LEARN=number>

<MAXLEARN=number>

<MAX | MAXMOMENTUM=number>

<MINLEARN=number >

<MOM | MOMENTUM=number>

<OUTEST=SAS-data-set>

<PREITER=integer>

<PRETECH=name>

<PRETIME=number>

<RANDBIAS|NORANDBIAS>

<RANDOUT|NORANDOUT>

<RANDOM=integer>;

Required Argument

integer

Specifies the number of preliminary optimizations.



Options

ACCEL | ACCELERATE=number

Specifies the rate of increase of learning for the RPROP optimization technique.



Range:

number > 1


Default:

1.2


DECEL | DECELERATE=number

Specifies the rate of decrease of learning for the RPROP optimization technique.



Range:

0 < number < 1



Default:

0.5


INEST=SAS-data-set

Specifies the input data set that contains some or all weights. Any weights in the INEST= data set

that have missing values are assigned values according to the RANDOM=, RANDOUT, and

RANDBIAS options, as well as the options that pertain to random number distributions that you

specify in the Random statements.

LEARN=number

Specifies the learning rate for BPROP or the initial learning rate for QPROP and RPROP.



Range:

number > 0

Default:

0.1


MAXLEARN=number

Specifies the maximum learning rate for RPROP.



Range:

number > 0

Default:

Reciprocal of the square root of the machine epsilon



MAXMOM | MAXMOMENTUM=number

Specifies the maximum momentum for BPROP.



Range:

number > 0

Default:

1.75


MINLEARN=number

Specifies the minimum learning rate for RPROP.



Range:

number > 0

Default:

Square root of the machine epsilon



MOM | MOMENTUM=number

Specifies the momentum for BPROP.



Range:

0   number < 1




Default:

For BPROP: 0.9; for RPROP: 0.1



OUTEST=SAS-data-set

Specifies the output data set that contains all the weights.



PREITER=integer

Specifies the maximum number of iterations in each preliminary optimization.



Default:

10

PRETECH | TECHNIQUE=name

Specifies the optimization technique. See 

TRAIN Statement

.

Default:

Same as TECH= in the TRAIN statement.



PRETIME=number

Specifies the amount of time after which training stops.



RANDBIAS | NORANDBIAS

Specifies whether to randomize output biases.



Default:

NORANDBIAS, which sets bias to the inverse activation function of the

target mean.

[NORANDBIAS overrides whatever you specify in the RANDOM

statement.]

RANDOM=integer

Specifies the random number seed.



Default:

0

RANDOUT | NORANDOUT

Specifies whether to randomize the output connection weights.

Default:

NORANDOUT, which sets weights to 0.

[NORANDOUT overrides whatever you specify in the RANDOM

statement.]

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




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