C++ 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 123456]
oCEnvironment::_envStructThe environment structure
oCAbstractCreatorInterface class used by the Factory class to register and create objects of a specific class
oCAlgorithmContainerIfaceImplements 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
oCAlgorithmIfaceAbstract class which defines interface for the library component related to data processing involving execution of the algorithms for analysis, modeling, and prediction
oCArgumentBase class to represent computation input and output arguments
oCAtomic< dataType >Class that represents an atomic object
oCBaseBase class for Intel(R) Data Analytics Acceleration Library objects
oCBatch< algorithmFPType, method >Provides methods to run implementations of the linear regression model-based prediction
oCBatchProvides methods to compute a quality metric set of an algorithm in the batch processing mode
oCBatch< algorithmFPType, method >Provides methods to run implementations of the ridge regression model-based prediction
oCBatchContainer< 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
oCBatchParameter< algorithmFPType, method >Class that specifies the parameters of the PCA algorithm in the batch computing mode
oCBlockDescriptor< DataType >Base class that manages buffer memory for read/write operations required by numeric tables
oCBlockDescriptor< DAAL_DATA_TYPE >
oCCollection< T >Class that implements functionality of the Collection container
oCCollection< SharedPtr< Error > >
oCCompressionIfaceAbstract interface class for compression and decompression
oCCompressionParameterParameters for compression and decompression
oCConfig< InputFeatureInfo, OutputFeatureInfo >Base class for modifier configuration
oCConfigIfaceAbstract class that defines interface of modifier configuration
oCContext< InputFeatureInfo, OutputFeatureInfo >Base class for modifier context
oCContextIfaceAbstract class that defines interface of modifier context
oCCSRBlockDescriptor< DataType >Base class that manages buffer memory for read/write operations required by CSR numeric tables
oCCSRNumericTableIfaceAbstract class that defines the interface of CSR numeric tables
oCCsvDataSourceOptionsOptions of CSV data source
oCDataSourceIfaceAbstract 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
oCDataSourceOptionsImpl< Value >Class that helps to define data source options
oCDeleterIfaceInterface for a utility class used within SharedPtr to delete an object when the object owner is destroyed
oCDenseNumericTableIfaceAbstract 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
oCDenseTensorIfaceAbstract 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
oCDistributed< step, algorithmFPType, method >Provides methods for neural network model-based training in the batch processing mode
oCDistributed< step, algorithmFPType, method >Computes moments of low order in the distributed processing mode
oCDistributed< step, algorithmFPType, method >Algorithm class for training naive Bayes model in the distributed processing mode
oCDistributed< step, algorithmFPType, method >Algorithm class for training naive Bayes model in the distributed processing mode
oCDistributed< step, algorithmFPType, method >Computes the results of the DBSCAN algorithm in the distributed processing mode
oCDistributed< step, algorithmFPType, method >Initializes the implicit ALS model in the distributed processing mode
oCDistributed< step, algorithmFPType, method >Computes the results of K-Means algorithm in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods for linear regression model-based training in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to train neural network model in the distributed processing mode using algorithmFPType precision arithmetic
oCDistributedContainer< 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
oCDistributedContainer< 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
oCDistributedContainer< computeStep, algorithmFPType, method, cpu >Class containing methods to compute the results of the PCA algorithm in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to compute naive Bayes training results in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of the QR decomposition algorithm
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to compute naive Bayes training results in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods for ridge regression model-based training in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to compute the result of DBSCAN algorithm in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of the SVD algorithm
oCDistributedContainer< step, algorithmFPType, method, cpu >Class that contains methods to run implicit ALS model-based prediction in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to compute the result of implicit ALS model-based training in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Class containing methods to compute the results of the implicit ALS initialization algorithm in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of K-Means algorithm. This class is associated with the daal::algorithms::kmeans::Distributed class and supports the method of K-Means computation in the distributed processing mode
oCDistributedContainer< step, algorithmFPType, method, cpu >Provides methods to run implementations of initialization of K-Means algorithm. This class is associated with the daal::algorithms::kmeans::init::Distributed class and supports the method of computing initial clusters for K-Means algorithm in the distributed processing mode
oCDistributedContainerIface< step >Class that spcifies interfaces of the correlation or variance-covariance matrix algorithm. This class is associated with daal::algorithms::covariance::DistributedIface class
oCDistributedInput< step >Input object for linear regression model-based training in the distributed processing mode
oCDistributedInput< step >Input objects of the neural network training algorithm in the distributed processing mode
oCDistributedInput< method >Input objects for the PCA algorithm in the distributed processing mode
oCDistributedInput< step >Input parameters of the distributed Covariance algorithm
oCDistributedInput< step >Input object for ridge regression model-based training in the distributed processing mode
oCDistributedInput< step >Input objects for the implicit ALS initialization algorithm in the distributed processing mode
oCDistributedInput< step >Input objects for the DBSCAN algorithm in the distributed processing mode
oCDistributedInput< step >Input objects for the implicit ALS training algorithm in the distributed processing mode
oCDistributedInput< step >Input objects for the rating prediction stage of the implicit ALS algorithm in the distributed processing mode
oCElementsPicker< T >Class that stores collection of elements of specified type and pointers to the elements of that collection corresponding to the indices provided in ElementsPicker::pick method
oCErrorClass that represents an error
oCErrorCollectionClass that represents an error collection
oCErrorDetailBase for error detail classes
oCexception
oCFactoryClass that provides factory functionality for objects implementing the SerializationIface interface. Used within deserialization functionality
oCFeatureAuxDataStructure for auxiliary data used for feature extraction
oCFeatureIdCollectionIfaceAbstract class that represents collection of feature ids
oCFeatureIdIfaceAbstract feature id interface
oCFeatureIdMappingIfaceAbstract class that defines interface for mapping feature id to feature index
oCFeatureIndexTraitsStatic class that contains auxiliary methods for FeatureIndex
oCFeatureIndicesIfaceAbstract class that defines interface for feature indices collection
oCFeatureModifierIface< Config, Context >General feature modifier interface
oCIndexData structure representing the indices of the dimension on which pooling is performed
oCIndicesData structure representing the indices of the two dimensions on which pooling is performed
oCIndicesData structure representing the indices of the two dimensions on which 2D transposed convolution is performed
oCIndicesData structure representing the indices of the two dimensions on which local contrast normalization is performed
oCIndicesData structure representing the indices of the two dimensions on which 2D locally connected is performed
oCIndicesData structure representing the indices of the two dimensions on which pooling is performed
oCIndicesData structure representing the indices of the three dimensions on which pooling is performed
oCIndicesData structure representing the indices of the two dimensions on which 2D convolution is performed
oCInitIfaceAbstract interface class that provides function for the initialization procedure
oCInitIfaceAbstract class that provides a functor for the initial procedure
oCInputAlgorithmsCollectionClass that implements functionality of the collection of quality metrics algorithms
oCInputIfaceAbstract class that specifies the interface of input objects for linear regression model-based training
oCInputIfaceAbstract class that specifies the interface of input objects for elastic net model-based training
oCInputIfaceAbstract class that specifies the interface of input objects for ridge regression model-based training
oCInputIfaceAbstract class that specifies the interface of input objects for lasso regression model-based training
oCIsSameType< U, V >
oCIsSameType< U, U >
oCKDBFeatureManagerContains KDB-specific commands
oCKernelBase class to represent algorithm implementation
oCKernelSizeData structure representing the size of the 1D subtensor from which the element is computed
oCKernelSizesData structure representing the size of the two-dimensional kernel subtensor
oCKernelSizesData structure representing the size of the 3D subtensor from which the element is computed
oCKernelSizesData structure representing the size of the two-dimensional kernel subtensor
oCKernelSizesData structure representing the size of the two-dimensional kernel subtensor
oCKernelSizesData structure representing the size of the 2D subtensor from which the element is computed
oCKeyValueCollection< T >Class that provides functionality of a key-value container for objects derived from the T with a key of the size_t type
oCLayerDescriptorClass defining descriptor for layer on both forward and backward stages and its parameters
oCLayerDescriptorClass defining descriptor for layer on forward stage
oCmap
oCModelBuilder< method >Builder for Model of the classifier trained by the multi_class_classifier::training::Batch algorithm
oCModelBuilder< modelFPType >Class for building model of the linear regression algorithm
oCModelBuilder< modelFPType >Class for building model of the logistic regression algorithm
oCModelBuilderModel Builder class for gradient boosted trees classification model
oCModelBuilder< modelFPType >Model Builder class for class SVM Model
oCModelBuilderModel Builder class for gradient boosted trees regression model
oCModelBuilderModel Builder class for Decision Forest Classification Model algorithm
oCModelBuilderModel Builder class for Decision Forest Classification Model algorithm
oCModifierIfaceAbstract interface class that defines the interface for a features modifier
oCNextLayersContains list of layer indices of layers following the current layer
oCNodeDescriptorStruct containing base description of node in descision tree
oCNumericTableIfaceAbstract 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
oCODBCDataSourceOptionsOptions of ODBC data source
oCOnlineContainer< 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
oCPackedArrayNumericTableIfaceAbstract class that defines the interface of symmetric matrices stored as a one-dimensional array
oCPaddingData structure representing the number of data elements to implicitly add to each side of the 1D subtensor on which pooling is performed
oCPaddingsData structure representing the number of data elements to implicitly add to each size of the two-dimensional subtensor on which 2D convolution is performed
oCPaddingsData 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
oCPaddingsData 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
oCPaddingsData structure representing the number of data elements to implicitly add to each size of the three-dimensional subtensor on which pooling is performed
oCPaddingsData structure representing the number of data elements to implicitly add to each side of the 2D subtensor on which pooling is performed
oCParameterParameters for the decision forest algorithm
oCParameter< algorithmFPType, method >Class that specifies the parameters of the algorithm in the batch computing mode
oCParameterParameters for the gradient boosted trees algorithm
oCParameterBase class to represent computation parameters. Algorithm-specific parameters are represented as derivative classes of the Parameter class
oCSharedPtr< 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
oCSharedPtr< Error >
oCSharedPtr< KernelErrorCollection >
oCSQLFeatureManagerInterprets the response of SQL data base and fill provided numeric table and dictionary
oCSQLFetchModeMode of fetching data from SQL table
oCStatusClass that holds the results of API calls. In case of API routine failure it contains the list of errors describing problems API encountered
oCStrideData structure representing the intervals on which the subtensors for pooling are computed
oCStridesData structure representing the intervals on which the subtensors for pooling are computed
oCStridesData structure representing the intervals on which the subtensors for 2D locally connected are selected
oCStridesData structure representing the intervals on which the subtensors for pooling are computed
oCStridesData structure representing the intervals on which the subtensors for 2D transposed convolution are selected
oCStridesData structure representing the intervals on which the subtensors for 2D convolution are selected
oCStringRowFeatureManagerIfaceAbstract 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
oCSubtensorDescriptor< DataType >Class with descriptor of the subtensor retrieved from Tensor getSubTensor function
oCTensorIfaceAbstract 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
oCTensorLayoutIfaceAbstract 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
oCTreeNodeVisitorInterface of abstract visitor used in tree traversal methods
oCTreeNodeVisitor< LeafNodeDescriptorType >Interface of abstract visitor used in tree traversal methods
oCTreeNodeVisitorInterface of abstract visitor used in tree traversal methods
oCValidationMetricIface
oCValueSizesData structure representing the value sizes of the two dimensions on which 2D transposed convolution is performed
oCAlgorithmContainerImpl
oCAlgorithmImpl
oCArgument
oCAtomic
oCBatch
oCBatch
oCBatchBase
oCBatchIface
oCCollection
oCCompressionParameter
oCCompressorImpl
oCConfig
oCConfigIface
oCContext
oCContextIface
oCDecompressorImpl
oCFamilyBatchBase
oCFeatureId
oCFeatureIdCollection
oCFeatureIdMapping
oCFeatureIndices
oCFeatureModifier
oCFeatureModifierIface
oCInitializerContainerIface
oCInitializerIface
oCInput
oCInput
oCInputDataCollection
oCInputIface
oCKernelIface
oCKeyValueDataCollection
oCKeyValueInputCollection
oCLayerContainerIfaceImpl
oCLayerIface
oCLayerIfaceImpl
oCModel
oCModelImpl
oCNodeDescriptor
oCOnline
oCOnline
oCParameter
oCParameter
oCParameterBase
oCPartialResult
oCResult
oCResult
oCResultCollection
oCSerializationIface
\CSharedPtr

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