Online Processing
Online processing computation mode assumes that data arrives in blocks 
.
.Computation of low order moments in the online processing mode follows the general computation schema
for online processing described in Algorithms.
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.Input ID | Input |
|---|---|
data | Pointer to the numeric table of size  that represents the current data block.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:
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:
|
initializationProcedure | Not applicable | The procedure for setting initial parameters of the algorithm in the online processing mode. By default, the algorithm does the following initialization:
|
estimatesToCompute | estimatesAll | Estimates to be computed by the algorithm:
|
Partial Results
The low order moments algorithm in the online processing mode calculates partial results 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 |
|---|---|
nObservations | Pointer to the  numeric table that contains the number of rows processed so far.By default, this result is an object of the HomogenNumericTable class, but you can define the result
as an object of any class derived from NumericTable except CSRNumericTable . |
Partial characteristics computed so far, each in a 
numeric table.
By default, each table is an object of the
numeric table.
By default, each table is an object of the HomogenNumericTable
class, but you can define the tables as objects
of any class derived from NumericTable
except PackedSymmetricMatrix
, PackedTriangularMatrix
, and CSRNumericTable
.Result ID | Result |
|---|---|
partialMinimum | Partial minimums |
partialMaximum | Partial maximums |
partialSum | Partial sums |
partialSumSquares | Partial sums of squares |
partialSumSquaresCentered | Partial sums of squared differences from the means |
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.Each result is a pointer to the numeric table that contains characteristics for each feature in the data set.
By default, the tables are objects of the
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
.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 |