Online Processing

Online processing computation mode assumes that data arrives in blocks i = 1, 2, 3, … nblocks.

PCA computation in the online processing mode follows the general computation schema for online processing described in Algorithms.

Algorithm Input

The PCA algorithm in the online processing mode 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 ni x p numeric table that represents the current data block. The input can be an object of any class derived from NumericTable.

Algorithm Parameters

The PCA algorithm in the online processing mode has the following parameters, depending on the computation method parameter method:

Parameter

method

Default Value

Description

algorithmFPType

defaultDense or svdDense

float

The floating-point type that the algorithm uses for intermediate computations. Can be float or double.

method

Not applicable

defaultDense

Available methods for PCA computation:

  • defaultDense - the correlation method
  • svdDense - the SVD method

initializationProcedure

defaultDense

Not applicable

The procedure for setting initial parameters of the algorithm in the online processing mode. By default, the algorithm initializes nObservationsCorrelation, sumCorrelation, and crossProductCorrelation with zeros.

svdDense

Not applicable

The procedure for setting initial parameters of the algorithm in the online processing mode. By default, the algorithm initializes nObservationsSVD, sumSVD, and sumSquaresSVD with zeros.

covariance

defaultDense

SharedPtr<covariance::Online<algorithmFPType, covariance::defaultDense> >

The correlation and variance-covariance matrices algorithm to be used for PCA computations with the correlation method. For details, see Correlation and Variance-covariance Matrices. Online Processing.

Partial Results

The PCA algorithm in the online processing mode calculates partial results described below. They depend on the computation method. 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

Correlation method (defaultDense):

nObservationsCorrelation

Pointer to the 1 x 1 numeric table with the number of observations processed so far. By default, this result is an object of the HomogenNumericTable class, but you can define it as an object of any class derived from NumericTable except CSRNumericTable.

crossProductCorrelation

Pointer to the p x p numeric table with the partial cross-product matrix computed so far. By default, this table is an object of the HomogenNumericTable class, but you can define it as an object of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

sumCorrelation

Pointer to the 1 x p numeric table with partial sums computed so far. By default, this table is an object of the HomogenNumericTable class, but you can define it as an object of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

SVD method (svdDense):

nObservationsSVD

Pointer to the 1 x 1 numeric table with the number of observations processed so far. By default, this result is an object of the HomogenNumericTable class, but you can define it as an object of any class derived from NumericTable except CSRNumericTable.

sumSVD

Pointer to the 1 x p numeric table with partial sums computed so far. By default, this table is an object of the HomogenNumericTable class, but you can define it as an object of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

sumSquaresSVD

Pointer to the 1 x p numeric table with partial sums of squares computed so far. By default, this table is an object of the HomogenNumericTable class, but you can define it as an object of any class derived from NumericTable except PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

Algorithm Output

The PCA algorithm in the online processing mode calculates the 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

eigenvalues

Pointer to the 1 x p numeric table that contains eigenvalues in the descending order. 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 PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

eigenvectors

Pointer to the p x p numeric table that contains eigenvectors in the row-major order. 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 PackedSymmetricMatrix, PackedTriangularMatrix, and CSRNumericTable.

Examples

C++:

Java*:

Python*:

For more complete information about compiler optimizations, see our Optimization Notice.
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