SAP HANA Predictive Analysis Library (PAL)

The following parameters are optional. If a parameter is not specified, PAL will use its default value.
Table 74:
Name Data Type Default Value Description
MAX_ITERATION Integer 1000 plus 500 times the
number of neurons in the lattice
Maximum number of iterations.
Note that the training might
not converge if this value is
too small, for example, less
than 1000.
CONVERGENCE_CRITERION Double 1.0e-6 If the largest difference of
the successive maps is less
than this value, the calculation
is regarded as convergence,
and SOM is completed
consequently.
NORMALIZATION Integer 0 Normalization type:
●
●
●
0: No
1: Transform to new
range (0.0, 1.0)
2: Z-score normalization
THREAD_NUMBER Integer 1 Number of threads.
RAMDOM_SEED Integer -1 ● -1: Random
●
●
0: Sets every weight to
zero
Other value: Uses this
value as seed
HEIGHT_OF_MAP Integer 10 Indicates the height of the
map.
WIDTH_OF_MAP Integer 10 Indicates the width of the
map.
KERNEL_FUNCTION Integer 1 Represents the neighborhood
kernel function.
●
●
1: Gaussian
2: Bubble/Flat
ALPHA Double 0.5 Specifies the learning rate.
LEARNING_RATE Integer 1 Indicates the decay function
for learning rate.
●
●
1: Exponential
2: Linear
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 105