Batch Processing

Algorithm Input

The low order moments 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.

Algorithm Input for Low Order Moments (Batch Processing)

Input ID	Input
data	Pointer to the numeric table of size \(n \times p\) to compute moments for. While the input for defaultDense, singlePassDense, or sumDense method can be an object of any class derived from NumericTable, the input for fastCSR, singlePassCSR, or sumCSR method can only be an object of the CSRNumericTable class.

Algorithm Parameters

The low order moments algorithm has the following parameters:

Algorithm Parameters for Low Order Moments (Batch Processing)

Parameter	Default Valude	Description
algorithmFPType	float	The floating-point type that the algorithm uses for intermediate computations. Can be float or double.
method	defaultDense	Available methods for computation of low order moments: For CPU: defaultDense - default performance-oriented method singlePassDense - implementation of the single-pass algorithm proposed by D.H.D. West sumDense - implementation of the algorithm in the cases where the basic statistics associated with the numeric table are pre-computed sums; returns an error if pre-computed sums are not defined fastCSR - performance-oriented method for CSR numeric tables singlePassCSR - implementation of the single-pass algorithm proposed by D.H.D. West; optimized for CSR numeric tables sumCSR - implementation of the algorithm in the cases where the basic statistics associated with the numeric table are pre-computed sums; optimized for CSR numeric tables; returns an error if pre-computed sums are not defined For GPU: defaultDense - default performance-oriented method
estimatesToCompute	estimatesAll	Estimates to be computed by the algorithm: estimatesAll - all supported moments estimatesMinMax - minimum and maximum estimatesMeanVariance - mean and variance

Algorithm Output

The low order moments algorithm calculates the results described in the following table. Pass the Result ID as a parameter to the methods that access the results of your algorithm. For more details, see Algorithms.

Note

Each result is a pointer to the \(1 \times p\) numeric table that contains characteristics for each feature in the data set. By default, the tables are objects of the HomogenNumericTable class, but you can define each table as an object of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

Algorithm Output for Low Order Moments (Batch Processing)

Result ID	Characteristic
minimum	Minimums
maximum	Maximums
sum	Sums
sumSquares	Sums of squares
sumSquaresCentered	Sums of squared differences from the means
mean	Estimates for the means
secondOrderRawMoment	Estimates for the second order raw moments
variance	Estimates for the variances
standardDeviation	Estimates for the standard deviations
variation	Estimates for the variations

Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex​. Notice revision #20201201