Python* API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 123456789]
 C_1
 CAlgorithmContainerIfaceImplImplements the abstract interface AlgorithmContainerIfaceImpl
 CAlgorithmIfaceAbstract class which defines interface for the library component related to data processing involving execution of the algorithms for analysis, modeling, and prediction
 CArgumentBase class to represent computation input and output arguments
 CBackwardLayersClass that implements functionality of the Collection container
 CBaseBase class for Intel(R) Data Analytics Acceleration Library objects
 CBasicStatisticsDataCollectionBasic statistics for each column of original Numeric Table
 CBatchPredict AdaBoost classification results
 CBatchProvides methods to compute a quality metric set of an algorithm in the batch processing mode
 CBatchPredicts BrownBoost classification results
 CBatchTrains model of the BrownBoost algorithms in the batch processing mode
 CBatchTrains model of the AdaBoost algorithms in batch mode
 CBatchPredicts LogitBoost classification results
 CBatchTrains model of the LogitBoost algorithms in the batch processing mode
 CBlockDescriptorBase class that manages buffer memory for read/write operations required by numeric tables
 CCategoricalFeatureDictionary
 CCollectionClass that implements functionality of the Collection container
 CCompressionIfaceAbstract interface class for compression and decompression
 CCompressionParameterParameters for compression and decompression
 CCSRBlockDescriptorBase class that manages buffer memory for read/write operations required by CSR numeric tables
 CCSRNumericTableIfaceAbstract class that defines the interface of CSR numeric tables
 CCsvDataSourceOptionsOptions of CSV data source
 CDataBlockClass that stores a pointer to a byte array and its size
 CDataSourceIfaceAbstract interface class that defines the interface for a data management component responsible for representation of data in the raw format
 CDenseNumericTableIfaceAbstract interface class for a data management component responsible for accessing data in the numeric format
 CDenseTensorIfaceAbstract interface class for a data management component responsible for accessing data in the numeric format
 CDistributedTrains the implicit ALS model in the first step of the distributed processing mode
 CDistributedInitializes the implicit ALS model in the first step of the distributed processing mode
 CDistributedComputes the results of K-Means algorithm in the first step of the distributed processing mode
 CDistributedProvides methods for neural network model-based training in the batch processing mode
 CDistributedBaseBase class representing K-Means algorithm initialization in the distributed processing mode
 CDistributedInputInput object for ridge regression model-based training in the distributed processing mode
 CDistributedInputInput object for linear regression model-based training in the distributed processing mode
 CDistributedParameterClass that specifies the parameters of the PCA algorithm in the distributed computing mode
 CDistributedPrediction
 CDistributedStep2LocalPlusPlusBaseBase class representing K-Means algorithm initialization in the distributed processing mode
 CErrorClass that represents an error
 CExceptionClass that represents an exception
 CFeatureAuxDataStructure for auxiliary data used for feature extraction
 CFeatureModifierBase class for feature modifier, intended for inheritance from the user side
 CFeatureModifierIfaceSpecialization of modifiers.FeatureModifierIface for CSV feature modifier
 CForwardLayersClass that implements functionality of the Collection container
 CIndexData structure representing the indices of the dimension on which pooling is performed
 CIndicesData structure representing the indices of the two dimensions on which 2D convolution is performed
 CIndicesData structure representing the indices of the two dimensions on which local contrast normalization is performed
 CIndicesData structure representing the indices of the two dimensions on which 2D locally connected is performed
 CIndicesData structure representing the indices of the two dimensions on which pooling is performed
 CIndicesData structure representing the indices of the three dimensions on which pooling is performed
 CIndicesData structure representing the indices of the two dimensions on which pooling is performed
 CIndicesData structure representing the indices of the two dimensions on which 2D transposed convolution is performed
 CInitializerContainerIfaceClass that specifies interfaces of implementations of the neural network weights and biases initializer
 CInitIfaceAbstract interface class that provides function for the initialization procedure
 CInitIfaceAbstract class that provides a functor for the initial procedure
 CInputAlgorithmsCollectionClass that implements functionality of the collection of quality metrics algorithms
 CInputDataCollectionClass that implements functionality of the collection of input objects of the quality metrics algorithm
 CInputIfaceAbstract class that specifies the interface of input objects for linear regression model-based training
 CInputIfaceAbstract class that specifies the interface of input objects for ridge regression model-based training
 Cinterface2_OnlineAlgorithm class for training the classifier model in the online processing mode
 CKernelBase class to represent algorithm implementation
 CKernelErrorCollectionClass that represents a kernel error collection (collection that cannot throw exceptions)
 CKernelSizeData structure representing the size of the 1D subtensor from which the element is computed
 CKernelSizesData structure representing the size of the two-dimensional kernel subtensor
 CKernelSizesData structure representing the size of the two-dimensional kernel subtensor
 CKernelSizesData structure representing the size of the two-dimensional kernel subtensor
 CKernelSizesData structure representing the size of the 2D subtensor from which the element is computed
 CKernelSizesData structure representing the size of the 3D subtensor from which the element is computed
 CKeyValueCollectionClass that provides functionality of a key-value container for objects derived from the T with a key of the size_t type
 CLayerContainerIfaceImplProvides methods of base container for forward layers
 CLayerDescriptorClass defining descriptor for layer on both forward and backward stages and its parameters
 CLayerDescriptorClass defining descriptor for layer on forward stage
 CModifierIfaceAbstract interface class that defines the interface for a features modifier
 CNextLayersContains list of layer indices of layers following the current layer
 CNumericTableIfaceAbstract interface class for a data management component responsible for representation of data in the numeric format
 CODBCDataSourceOptionsOptions of ODBC data source
 COnlineComputes the results of the PCA SVD algorithm
 COnlineProvides methods for the regression model-based training in the online processing mode
 COnlineComputes results of the SVD algorithm in the online processing mode
 COnlineComputes moments of low order in the online processing mode
 COnlineComputes the results of the QR decomposition algorithm in the online processing mode
 COnlineAlgorithm class for training the classifier model in the online processing mode
 COnlineImplAbstract class that specifies interface of the algorithms for computing correlation or variance-covariance matrix in the online processing mode
 COnlineParameterClass that specifies the parameters of the PCA SVD algorithm in the online computing mode
 CPackedArrayNumericTableIfaceAbstract class that defines the interface of symmetric matrices stored as a one-dimensional array
 CPaddingData structure representing the number of data elements to implicitly add to each side of the 1D subtensor on which pooling is performed
 CPaddingsData structure representing the number of data elements to implicitly add to each size of the two-dimensional subtensor on which 2D convolution is performed
 CPaddingsData structure representing the number of data elements to implicitly add to each size of the two-dimensional subtensor on which 2D transposed convolution is performed
 CPaddingsData structure representing the number of data elements to implicitly add to each size of the two-dimensional subtensor on which 2D locally connected is performed
 CPaddingsData structure representing the number of data elements to implicitly add to each side of the 2D subtensor on which pooling is performed
 CPaddingsData structure representing the number of data elements to implicitly add to each size of the three-dimensional subtensor on which pooling is performed
 CParameterBase class to represent computation parameters
 CParameterParameters for the decision forest algorithm
 CParameterParameters for the gradient boosted trees algorithm
 CSerializationDesc
 CSQLFeatureManagerInterprets the response of SQL data base and fill provided numeric table and dictionary
 CStatus
 CStrideData structure representing the intervals on which the subtensors for pooling are computed
 CStridesData structure representing the intervals on which the subtensors for 2D locally connected are selected
 CStridesData structure representing the intervals on which the subtensors for 2D convolution are selected
 CStridesData structure representing the intervals on which the subtensors for 2D transposed convolution are selected
 CStridesData structure representing the intervals on which the subtensors for pooling are computed
 CStridesData structure representing the intervals on which the subtensors for pooling are computed
 CSubtensorDescriptorClass with descriptor of the subtensor retrieved from Tensor getSubTensor function
 CTensorIfaceAbstract interface class for a data management component responsible for representation of data in the numeric format
 CTensorLayoutIfaceAbstract interface class for a data management component responsible for representation of data layout in the tensor
 CTreeNodeVisitorInterface of abstract visitor used in tree traversal methods
 CTreeNodeVisitorInterface of abstract visitor used in tree traversal methods
 CValidationMetricIface
 CValueSizesData structure representing the value sizes of the two dimensions on which 2D transposed convolution is performed

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