Developer Guide for Intel® Data Analytics Acceleration Library 2018 Update 2
The min-max normalization algorithm accepts the input 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. |
The min-max normalization algorithm has the following parameters:
Parameter |
Default Value |
Description |
|
---|---|---|---|
algorithmFPType |
float |
The floating-point type that the algorithm uses for intermediate computations. Can be float or double. |
|
method |
defaultDense |
Performance-oriented computation method, the only method supported by the algorithm. |
|
lowerBound |
0.0 |
The lower bound of the range to which the normalization scales values of the features. |
|
upperBound |
1.0 |
The upper bound of the range to which the normalization scales values of the features. |
|
moments |
SharedPtr<low_order_moments::Batch<algorithmFPType, low_order_moments::defaultDense> > |
Pointer to the low order moments algorithm that computes minimums and maximums to be used for min-max normalization with the defaultDense method. For more details, see Moments of Low Order > Batch Processing. |
The min-max normalization algorithm calculates the result 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. |