The arboretum procedure



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documentation -> From cyber-crime to insider trading, digital investigators are increasingly being asked to
documentation -> EnCase Forensic Transform Your Investigations
documentation -> File Sharing Documentation Prepared by Alan Halter Created: 1/7/2016 Modified: 1/7/2016
documentation -> Gaia Data Release 1 Documentation release 0

VALID | VALIDATION

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

variable.

TEST


Specifies that the DATA= data set is a test set. The data set must contain the target variable.

SCORE


Specifies that residuals, error functions, and fit statistics are not produced. The data set does

not have to contain the target variable.



Default:

TEST, except as follows:

TRAIN when the DATA= data set in the PROC statement is the same as

the DATA= data set in the SCORE statement. Specifying TRAIN

with any data set other than the actual training set is an error.

VALID when the DATA= data set in the SCORE statement is the same as

the VALIDATA= data set in the PROC statement.

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




The NEURAL Procedure

SET Statement

Sets the value of the weight-list to number. The SET statement does not freeze weights, so

subsequent training may change the values of the weights specified in a SET statement.

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

affect only that statement.



SET weight-list number;

Required Arguments

weight-list

Specifies the list of weights to be affected or changed.



number

Specifies the number to which the weight-list is set.

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



The NEURAL Procedure

SHOW Statement

Prints information about the network.

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.

SHOWWEIGHTS

STATEMENTS

Options

Specify at least one:



STATEMENTS

Prints statements that can be used with the NEURAL procedure to reproduce the network.



WEIGHTS

Prints the network weights.

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



The NEURAL Procedure

TARGET Statement

Defines an output layer.

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

affect only that statement.



Alias: OUTPUT

TARGET | OUTPUT variable-list /

<ACT=activation-function>

<BIAS|NOBIAS >

<COMBINE=combination-function>

<ERROR=keyword>

<ID=name>

<LEVEL=value>

<MESTA=number>

<MESTCON=number>

<SIGMA=number>

<STD=method>;

Required Arguments

variable-list

Specifies the target variables.



ID=name

Specifies the identifier for the layer.



Options

ACT=activation-function

Specifies the activation function. See 

Activation Functions

.



Default:

Depends on the measurement level, as follows:

If LEVEL=INTERVAL, then the default is IDENTITY.

If LEVEL=ORDINAL then the default is LOGISTIC.

If LEVEL=NOMINAL, then the default is MLOGISTIC

(For Error=MBERNOULLI, MENTROPY, or MULTINOMIAL, the

only activation function allowed is MLOGISTIC.)

BIAS | NOBIAS

Specifies whether to use bias (or not to use bias).



Default:

BIAS


COMBINE=combination-function

Specifies the combination function. See 

Combination Functions

.

ERROR=keyword

Specifies the Error function. Default is NORMAL for LEVEL=INTERVAL; otherwise, default is

MBERNOULLI. For more information, see the Error Functions table that follows.



Error Functions

KEYWORD

TARGET

DESCRIPTION

Functions with scale parameters :

NORmal

any


Normal

distribution

CAUchy

any


Cauchy

distribution

LOGistic

any


Logistic

distribution

HUBer

any


Huber M

estimator

BIWeight

any


Biweight M

estimator

WAVe

any


Wave M

estimator




GAMma

>0

Gamma



distribution

POIsson


0

Poisson


distribution

Functions with no scale parameter

BERnoulli

0,1


Bernoulli

distribution

(binomial with

one trial)

BINomial

0

Binomial



distribution

ENTropy


0-1

Cross or relative

entropy for

independent

targets

MBErnoulli



0,1

Multiple


Bernoulli

(multinomial

with one trial)

MULtinomial

0

Multinomial



distribution

MENtropy


0-1

Cross or relative

entropy for

targets that sum

to 1

(Kullback-Leibler



divergence)

LEVEL=value

Specifies the measurement level, where value can be:

NOMINAL|NOM

Nominal.


ORDINAL|ORD

Ordinal.


INTERVAL|INT

Interval.





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