C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 3

Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 12345]
 CEnvironment::_envStructThe environment structure
 CAbstractCreatorInterface class used by the Factory class to register and create objects of a specific class
 CAlgorithmContainerIfaceImplements the abstract interface AlgorithmContainerIface. It is associated with the Algorithm class and supports the methods for computation and finalization of the algorithm results in the batch, distributed, and online modes
 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
 CAtomic< dataType >Class that represents an atomic object
 CBaseBase class for Intel(R) Data Analytics Acceleration Library objects
 CBatchProvides methods to compute a quality metric set of an algorithm in the batch processing mode
 CBatch< algorithmFPType, method >Provides methods to run implementations of the ridge regression model-based prediction
 CBatch< algorithmFPType, method >Provides methods to run implementations of the linear regression model-based prediction
 CBatchContainer< algorithmFPType, method, cpu >Provides methods to run implementations of the correlation or variance-covariance matrix algorithm. This class is associated with daal::algorithms::covariance::Batch class
 CBatchParameter< algorithmFPType, method >Class that specifies the parameters of the PCA algorithm in the batch computing mode
 CBlockDescriptor< DataType >Base class that manages buffer memory for read/write operations required by numeric tables
 CBlockDescriptor< DAAL_DATA_TYPE >
 CCollection< T >Class that implements functionality of the Collection container
 CCollection< SharedPtr< Error > >
 CCompressionIfaceAbstract interface class for compression and decompression
 CCompressionParameterParameters for compression and decompression
 CCSRBlockDescriptor< DataType >Base class that manages buffer memory for read/write operations required by CSR numeric tables
 CCSRNumericTableIfaceAbstract class that defines the interface of CSR numeric tables
 CDataSourceIfaceAbstract interface class that defines the interface for a data management component responsible for representation of data in the raw format. This class declares the most generic methods for data access
 CDeleterIfaceInterface for a utility class used within SharedPtr to delete an object when the object owner is destroyed
 CDenseNumericTableIfaceAbstract interface class for a data management component responsible for accessing data in the numeric format. This class declares specific methods to access data in a dense homogeneous form
 CDenseTensorIfaceAbstract interface class for a data management component responsible for accessing data in the numeric format. This class declares specific methods to access Tensor data in a dense homogeneous form
 CDistributed< step, algorithmFPType, method >Initializes the implicit ALS model in the distributed processing mode
 CDistributed< step, algorithmFPType, method >Computes the results of the K-Means algorithm in the distributed processing mode
 CDistributed< step, algorithmFPType, method >Computes moments of low order in the distributed processing mode
 CDistributed< step, algorithmFPType, method >Provides methods for neural network model-based training in the batch processing mode
 CDistributed< step, algorithmFPType, method >Algorithm class for training naive Bayes model in the distributed processing mode
 CDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to compute the results of the implicit ALS initialization algorithm in the distributed processing mode
 CDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of the QR decomposition algorithm
 CDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods for ridge regression model-based training in the distributed processing mode
 CDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of the SVD algorithm
 CDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods for linear regression model-based training in the distributed processing mode
 CDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of the low order moments algorithm in the distributed processing mode. This class is associated with daal::algorithms::low_order_moments::Distributed class
 CDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of the correlation or variance-covariance matrix algorithm in the distributed processing mode. This class is associated with daal::algorithms::covariance::Distributed class
 CDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to train neural network model in the distributed processing mode using algorithmFPType precision arithmetic
 CDistributedContainer< step, algorithmFPType, method, cpu >Class that contains methods to run implicit ALS model-based prediction in the distributed processing mode
 CDistributedContainer< computeStep, algorithmFPType, method, cpu >Class containing methods to compute the results of the PCA algorithm in the distributed processing mode
 CDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to compute the result of implicit ALS model-based training in the distributed processing mode
 CDistributedContainerIface< step >Class that spcifies interfaces of the correlation or variance-covariance matrix algorithm. This class is associated with daal::algorithms::covariance::DistributedIface class
 CDistributedInput< method >Input objects for the PCA algorithm in the distributed processing mode
 CDistributedInput< step >Input parameters of the distributed Covariance algorithm
 CDistributedInput< step >Input objects for the implicit ALS initialization algorithm in the distributed processing mode
 CDistributedInput< step >Input object for ridge regression model-based training in the distributed processing mode
 CDistributedInput< step >Input object for linear regression model-based training in the distributed processing mode
 CDistributedInput< step >Input objects of the neural network training algorithm in the distributed processing mode
 CDistributedInput< step >Input objects for the implicit ALS training algorithm in the distributed processing mode
 CDistributedInput< step >Input objects for the rating prediction stage of the implicit ALS algorithm in the distributed processing mode
 CErrorClass that represents an error
 CErrorCollectionClass that represents an error collection
 CErrorDetailBase for error detail classes
 Cexception
 CFactoryClass that provides factory functionality for objects implementing the SerializationIface interface. Used within deserialization functionality
 CFeatureAuxDataStructure for auxiliary data used for feature extraction
 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 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 two dimensions on which local contrast normalization 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
 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
 CInputIfaceAbstract class that specifies the interface of input objects for ridge regression model-based training
 CInputIfaceAbstract class that specifies the interface of input objects for linear regression model-based training
 CIsSameType< U, V >
 CIsSameType< U, U >
 CKDBFeatureManagerContains KDB-specific commands
 CKernelBase class to represent algorithm implementation
 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 2D subtensor from which the element is computed
 CKernelSizesData structure representing the size of the 3D subtensor from which the element is computed
 CKernelSizesData structure representing the size of the two-dimensional kernel subtensor
 CKeyValueCollection< T >Class that provides functionality of a key-value container for objects derived from the T with a key of the size_t type
 CLayerDescriptorClass defining descriptor for layer on both forward and backward stages and its parameters
 CLayerDescriptorClass defining descriptor for layer on forward stage
 Cmap
 CModifierIfaceAbstract interface class that defines the interface for a features modifier
 CMySQLFeatureManagerContains MySQL-specific commands
 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. This class declares the most general methods for data access
 COnlineContainer< algorithmFPType, method, cpu >Provides methods to run implementations of the correlation or variance-covariance matrix algorithm. This class is associated with daal::algorithms::covariance::Online class
 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 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 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 three-dimensional subtensor on which pooling is performed
 CParameter< algorithmFPType, method >Class that specifies the parameters of the algorithm in the batch computing mode
 CParameterBase class to represent computation parameters. Algorithm-specific parameters are represented as derivative classes of the Parameter class
 CParameterParameters for the decision forest algorithm
 CParameterParameters for the gradient boosted trees algorithm
 CSharedPtr< T >Shared pointer that retains shared ownership of an object through a pointer. Several SharedPtr objects may own the same object. The object is destroyed and its memory deallocated when either of the following happens:
1) the last remaining SharedPtr owning the object is destroyed.
2) the last remaining SharedPtr owning the object is assigned another pointer via operator=.
The object is destroyed using the delete operator
 CSharedPtr< Error >
 CSharedPtr< KernelErrorCollection >
 CStatusClass that holds the results of API calls. In case of API routine failure it contains the list of errors describing problems API encountered
 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 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 2D convolution are selected
 CStridesData structure representing the intervals on which the subtensors for pooling are computed
 CStringRowFeatureManagerIfaceAbstract interface class that defines the interface to parse and convert the raw data represented as a string into a numeric format. The string must represent a row of data, a dictionary, or a vector of features
 CSubtensorDescriptor< DataType >Class 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. This class declares the most general methods for data access
 CTensorLayoutIfaceAbstract interface class for a data management component responsible for representation of data layout in the tensor. This class declares the most general methods for data access
 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
 CAlgorithmContainerImpl
 CAlgorithmImpl
 CArgument
 CAtomic
 CBatch
 CBatchBase
 CBatchIface
 CCollection
 CCompressionParameter
 CCompressorImpl
 CDecompressorImpl
 CInitializerContainerIface
 CInitializerIface
 CInput
 CInputDataCollection
 CInputIface
 CKernelIface
 CKeyValueDataCollection
 CKeyValueInputCollection
 CLayerContainerIfaceImpl
 CLayerIface
 CLayerIfaceImpl
 CModel
 CModelImpl
 COnline
 CParameter
 CParameterBase
 CPartialResult
 CResult
 CResultCollection
 CSerializationIface

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