Intel® oneAPI Data Analytics Library Developer Guide and Reference

Developer Guide and Reference

  • 2021.2
  • 03/26/2021
  • Public Content
Contents

Correlation Distance Matrix

Given
n
 feature vectors LaTex Math image. of dimension Lmath:
p
, the problem is to compute the symmetric LaTex Math image. matrix LaTex Math image. of distances between feature vectors, where
LaTex Math image.
LaTex Math image.
LaTex Math image.
LaTex Math image.
LaTex Math image.

Batch Processing

Algorithm Input
The correlation distance matrix 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 LaTex Math image. numeric table for which the distance is computed.
The input can be an object of any class derived from
NumericTable
.
Algorithm Parameters
The correlation distance matrix 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.
Algorithm Output
The correlation distance matrix 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
correlationDistance
Pointer to the numeric table that represents the LaTex Math image. symmetric distance matrix LaTex Math image..
By default, the result is an object of the
PackedSymmetricMatrix
 class with the
lowerPackedSymmetricMatrix
 layout. However, you can define the result as an object of any class derived from
NumericTable
 except
PackedTriangularMatrix
 and
CSRNumericTable
.

Examples

C++ (CPU)
Batch Processing:
Java*
There is no support for Java on GPU.
Batch Processing:
Python*
Batch Processing:

Performance Considerations

To get the best overall performance when computing the correlation distance matrix:
  • If input data is homogeneous, provide the input data and store results in homogeneous numeric tables of the same type as specified in the
    algorithmFPType
     class template parameter.
  • If input data is non-homogeneous, use AOS layout rather than SOA layout.
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex​.
Notice revision #20201201

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.