Intel® oneAPI Data Analytics Library Developer Guide and Reference
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Min-max
Min-max normalization is an algorithm to linearly scale the observations by each feature (column) into the range 
.
Problem Statement
Given a set X of n feature vectors 
 of dimension p, the problem is to compute the matrix 
 where the j-th column 
 is obtained as a result of normalizing the column 
 of the original matrix as:
 
   where:
 
   
 
   a and b are the parameters of the algorithm.
Batch Processing
Algorithm Input
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  
            NOTE: 
            This table can be an object of any class derived from NumericTable. 
          |  
       
Algorithm Parameters
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 Batch Processing for Moments of Low Order.  |  
       
Algorithm Output
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  
            NOTE: 
            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. 
          |  
       
Examples
C++ (CPU)
Batch Processing:
Python*
Batch Processing:
.