Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
A combination function combines the values received from preceding nodes into a single number called
the net input. Both output and hidden layers are assigned combination functions.
The following combination functions are available.
Adds all the incoming values without using any weights or biases.
Is a linear combination of the incoming values and weights.
Is identical to the Linear combination function, except that the same connection weights are used
for each unit in the layer, although different units have different biases. EQSlopes is mainly used
for ordinal targets.
Is a radial basis function with equal heights and widths for all units in the layer.
Is a radial basis function with equal heights but unequal widths for all units in the layer.
Is a radial basis function with equal widths but unequal heights for all units in the layer.
Is a radial basis function with equal volumes for all units in the layer.
Is a radial basis function with unequal heights and widths for all units in the layer.
The following definitions apply to the Table of Combination Functions:
Are divided by the net inputs indexed by i.
The altitude of the jth unit
The width (bias) of the jth unit
A common bias shared by all units in the layer
The weight connecting the ith incoming value to the jth unit
The common weight for the ith input shared by all units in the layer
The ith incoming value
affect only that statement.
Specifies how to adjust the random biases for units with a LINEAR combination function. A
random bias is adjusted by multiplying by the function of the weights indicated by
adjustment-value, and dividing by the scale (RANSCALE=) of the distribution from which the
random bias was drawn. adjustment value can be one of the following:
Adjusts random initial biases for the sum of the absolute connection weights leading into
Adjusts random initial biases for the square root of the sum of squared connection weights
No bias adjustment.
Specifies an input data set that contains some or all of the 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. An INEST= data set will typically have been created by
using the OUTEST= option in a SAVE or a TRAIN statement from a previous execution of the
Divide random connection weights by
(fan-in of unit)** number
where the "fan-in" of a unit is the number of other units feeding into that unit, not counting the
bias or altitude.
0 for radial combination functions, otherwise .5
between 0 and 1
Specifies the output data set that contains all the initial weights.
Specifies whether to randomize output biases.
NORANDBIAS, which sets bias to the inverse activation function of the
Specifies the random number seed.
RANDOUT | NORANDOUT
Specifies whether to randomize the output connection weights.
Note: NORANDOUT overrides whatever you specify in the RANOPTIONS statement.
NORANDOUT, which sets weights to 0.
Specifies whether to randomize target scale estimates.