Developer Guide

Contents

Batch Processing

Algorithm Input

Z-score normalization algorithm accepts an input as described below. Pass the Input ID as a parameter to the methods that provide input for your algorithm. For more details, see Algorithms .
Input ID
Input
data
Pointer to the numeric table of size
n
x
p
. This table can be an object of any class derived from
NumericTable
.

Algorithm Parameters

Z-score normalization algorithm has the following parameters. Some of them are required only for specific values of the computation method parameter
method
:
Parameter
method
Default Value
Description
algorithm
FPType
defaultDense
or
sumDense
double
The floating-point type that the algorithm uses for intermediate computations. Can be
float
or
double
.
method
Not applicable
defaultDense
Available computation methods:
  • defaultDense
    - a performance-oriented method. Mean and variance are computed by low order moments algorithm. For details, see Moments of Low Order > Batch Processing .
  • sumDense
    - a method that uses the basic statistics associated with the numeric table of pre-computed sums. Returns an error if pre-computed sums are not defined.
moments
defaultDense
SharedPtr<low_order_moments::Batch<algorithmFPType, low_order_moments::defaultDense> >
Pointer to the low order moments algorithm that computes means and standard deviations to be used for Z-score normalization with the
defaultDense
method.
doScale
defaultDense
or
sumDense
true
If
true
, the algorithm applies both centering and scaling.
Otherwise, the algorithm provides only centering.
resultsToCompute
defaultDense
or
sumDense
none
Optional.
Pointer to the data collection containing the following key-value pairs for Z-score:
mean
means
variance
variances
Provide one of these values to request a single characteristic or use bitwise OR to request a combination of them.

Algorithm Output

Z-score normalization algorithm calculates the result as described below. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms .
Result ID
Result
normalizedData
Pointer to the
n
x
p
numeric table that stores the result of normalization. By default, the result is an object of the
HomogenNumericTable
class, but you can define the result as an object of any class derived from
NumericTable
except
PackedTriangularMatrix
,
PackedSymmetricMatrix
, and
CSRNumericTable
.
means
Optional.
Pointer to the 1 x
p
numeric table that contains mean values for each feature.
If the function result is not requested through the
resultsToCompute
parameter, the numeric table contains a
NULL
pointer.
variances
Optional.
Pointer to the 1 x
p
numeric table that contains variance values for each feature.
If the function result is not requested through the
resultsToCompute
parameter, the numeric table contains a
NULL
pointer.
By default, each numeric table specified by the collection elements is an object of the
HomogenNumericTable
class. You can also define the result as an object of any class derived from
NumericTable
, except for
PackedSymmetricMatrix
,
PackedTriangularMatrix
, and
CSRNumericTable
.

Product and Performance Information

1

Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

Notice revision #20110804