C++ API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

References | Namespaces | Classes | Enumerations | Functions

Contains a class for ridge regression model-based training. More...

References

 Batch
 
 Distributed
 
 Online
 

Namespaces

 daal::algorithms::ridge_regression::training
 Contains a class for ridge regression model-based training.
 
 daal::algorithms::ridge_regression::training::interface1
 Contains version 1.0 of the Intel(R) Data Analytics Acceleration Library (Intel(R) DAAL) interface.
 

Classes

class  InputIface
 Abstract class that specifies the interface of input objects for ridge regression model-based training. More...
 
class  Input
 Input objects for ridge regression model-based training More...
 
class  DistributedInput< step >
 Input object for ridge regression model-based training in the distributed processing mode More...
 
class  PartialResult
 Provides methods to access a partial result obtained with the compute() method of ridge regression model-based training in the online or distributed processing mode. More...
 
class  DistributedInput< step2Master >
 Input object for ridge regression model-based training in the second step of the distributed processing mode More...
 
class  Result
 Provides methods to access the result obtained with the compute() method of ridge regression model-based training. More...
 

Enumerations

enum  Method { defaultDense = 0, normEqDense = 0 }
 Computation methods for ridge regression model-based training. More...
 
enum  InputId { data = linear_model::training::data, dependentVariables = linear_model::training::dependentVariables }
 Available identifiers of input objects for ridge regression model-based training. More...
 
enum  Step2MasterInputId { partialModels }
 Available identifiers of input objects for ridge regression model-based training in the second step of the distributed processing mode. More...
 
enum  PartialResultID { partialModel }
 Available identifiers of a partial result of ridge regression model-based training. More...
 
enum  ResultId { model = linear_model::training::model }
 Available identifiers of the result of ridge regression model-based training. More...
 

Functions

virtual size_t getNumberOfFeatures () const =0
 
virtual size_t getNumberOfDependentVariables () const =0
 
 Input ()
 
data_management::NumericTablePtr get (InputId id) const
 
void set (InputId id, const data_management::NumericTablePtr &value)
 
size_t getNumberOfFeatures () const DAAL_C11_OVERRIDE
 
size_t getNumberOfDependentVariables () const DAAL_C11_OVERRIDE
 
services::Status check (const daal::algorithms::Parameter *par, int method) const DAAL_C11_OVERRIDE
 
daal::algorithms::ridge_regression::ModelPtr get (PartialResultID id) const
 
size_t getNumberOfFeatures () const
 
size_t getNumberOfDependentVariables () const
 
void set (PartialResultID id, const daal::algorithms::ridge_regression::ModelPtr &value)
 
template<typename algorithmFPType >
DAAL_EXPORT services::Status allocate (const daal::algorithms::Input *input, const daal::algorithms::Parameter *parameter, const int method)
 
template<typename algorithmFPType >
DAAL_EXPORT services::Status initialize (const daal::algorithms::Input *input, const daal::algorithms::Parameter *parameter, const int method)
 
services::Status check (const daal::algorithms::Input *input, const daal::algorithms::Parameter *par, int method) const DAAL_C11_OVERRIDE
 
services::Status check (const daal::algorithms::Parameter *par, int method) const DAAL_C11_OVERRIDE
 
data_management::DataCollectionPtr get (Step2MasterInputId id) const
 
void set (Step2MasterInputId id, const data_management::DataCollectionPtr &ptr)
 
void add (Step2MasterInputId id, const PartialResultPtr &partialResult)
 
size_t getNumberOfFeatures () const DAAL_C11_OVERRIDE
 
size_t getNumberOfDependentVariables () const DAAL_C11_OVERRIDE
 
services::Status check (const daal::algorithms::Parameter *parameter, int method) const DAAL_C11_OVERRIDE
 
ridge_regression::ModelPtr get (ResultId id) const
 
void set (ResultId id, const ridge_regression::ModelPtr &value)
 
template<typename algorithmFPType >
DAAL_EXPORT services::Status allocate (const daal::algorithms::Input *input, const Parameter *parameter, const int method)
 
template<typename algorithmFPType >
DAAL_EXPORT services::Status allocate (const daal::algorithms::PartialResult *partialResult, const Parameter *parameter, int method)
 
services::Status check (const daal::algorithms::Input *input, const daal::algorithms::Parameter *par, int method) const DAAL_C11_OVERRIDE
 
services::Status check (const daal::algorithms::PartialResult *pr, const daal::algorithms::Parameter *par, int method) const DAAL_C11_OVERRIDE
 

Enumeration Type Documentation

enum InputId

Enumerator
data 

Input data table

dependentVariables 

Values of the dependent variable for the input data

enum Method

Enumerator
defaultDense 

Normal equations method

normEqDense 

Normal equations method

enum PartialResultID

Enumerator
partialModel 

Partial model trained on the available input data

enum ResultId

Enumerator
model 

Linear regression model

enum Step2MasterInputId

Enumerator
partialModels 

Collection of partial models trained on local nodes

Function Documentation

void add ( Step2MasterInputId  id,
const PartialResultPtr &  partialResult 
)

Adds an input object for ridge regression model-based training in the second step of the distributed processing mode

Parameters
[in]idIdentifier of the input object
[in]partialResultInput object
DAAL_EXPORT services::Status allocate ( const daal::algorithms::Input *  input,
const daal::algorithms::Parameter *  parameter,
const int  method 
)

Allocates memory to store a partial result of ridge regression model-based training

Parameters
[in]inputInput object for the algorithm
[in]methodMethod of ridge regression model-based training
[in]parameterParameter of ridge regression model-based training
Returns
Status of computations
DAAL_EXPORT services::Status allocate ( const daal::algorithms::Input *  input,
const Parameter *  parameter,
const int  method 
)

Allocates memory to store the result of ridge regression model-based training

Parameters
[in]inputPointer to an object containing the input data
[in]parameterParameter of ridge regression model-based training
[in]methodComputation method for the algorithm
Returns
Status of computations
DAAL_EXPORT services::Status allocate ( const daal::algorithms::PartialResult *  partialResult,
const Parameter *  parameter,
int  method 
)

Allocates memory to store the result of ridge regression model-based training

Parameters
[in]partialResultPointer to an object containing the input data
[in]methodComputation method of the algorithm
[in]parameterParameter of ridge regression model-based training
Returns
Status of computations
services::Status check ( const daal::algorithms::Parameter *  par,
int  method 
) const

Checks an input object for the ridge regression algorithm

Parameters
[in]parAlgorithm parameter
[in]methodComputation method
Returns
Status of computations
services::Status check ( const daal::algorithms::Input *  input,
const daal::algorithms::Parameter *  par,
int  method 
) const

Checks a partial result of the ridge regression algorithm

Parameters
[in]inputInput object for the algorithm
[in]parParameter of the algorithm
[in]methodComputation method
Returns
Status of computations
services::Status check ( const daal::algorithms::Parameter *  par,
int  method 
) const

Checks a partial result of the ridge regression algorithm

Parameters
[in]parParameter of the algorithm
[in]methodComputation method
Returns
Status of computations
services::Status check ( const daal::algorithms::Parameter *  parameter,
int  method 
) const

Checks an input object for ridge regression model-based training in the second step of the distributed processing mode

Returns
Status of computations
services::Status check ( const daal::algorithms::Input *  input,
const daal::algorithms::Parameter *  par,
int  method 
) const

Checks the result of ridge regression model-based training

Parameters
[in]inputInput object for the algorithm
[in]parParameter of the algorithm
[in]methodComputation method
Returns
Status of computations
services::Status check ( const daal::algorithms::PartialResult *  pr,
const daal::algorithms::Parameter *  par,
int  method 
) const

Checks the result of the ridge regression model-based training

Parameters
[in]prPartialResult of the algorithm
[in]parParameter of the algorithm
[in]methodComputation method
Returns
Status of computations
data_management::NumericTablePtr get ( InputId  id) const

Returns an input object for ridge regression model-based training

Parameters
[in]idIdentifier of the input object
Returns
Input object that corresponds to the given identifier
daal::algorithms::ridge_regression::ModelPtr get ( PartialResultID  id) const

Returns a partial result of ridge regression model-based training

Parameters
[in]idIdentifier of the partial result
Returns
Partial result that corresponds to the given identifier
data_management::DataCollectionPtr get ( Step2MasterInputId  id) const

Gets an input object for ridge regression model-based training in the second step of the distributed processing mode

Parameters
[in]idIdentifier of the input object
Returns
Input object that corresponds to the given identifier
ridge_regression::ModelPtr get ( ResultId  id) const

Returns the result of ridge regression model-based training

Parameters
[in]idIdentifier of the result
Returns
Result that corresponds to the given identifier
virtual size_t getNumberOfDependentVariables ( ) const
pure virtual

Returns the number of dependent variables

Returns
Number of dependent variables

Implemented in DistributedInput< step2Master >, and Input.

size_t getNumberOfDependentVariables ( ) const
virtual

Returns the number of dependent variables

Returns
Number of dependent variables

Implements InputIface.

size_t getNumberOfDependentVariables ( ) const

Returns the number of dependent variables

Returns
Number of dependent variables
size_t getNumberOfDependentVariables ( ) const
virtual

Returns the number of dependent variables

Returns
Number of dependent variables

Implements InputIface.

virtual size_t getNumberOfFeatures ( ) const
pure virtual

Returns the number of columns in the input data set

Returns
Number of columns in the input data set

Implemented in DistributedInput< step2Master >, and Input.

size_t getNumberOfFeatures ( ) const
virtual

Returns the number of columns in the input data set

Returns
Number of columns in the input data set

Implements InputIface.

size_t getNumberOfFeatures ( ) const

Returns the number of columns in the input data set

Returns
Number of columns in the input data set
size_t getNumberOfFeatures ( ) const
virtual

Returns the number of columns in the input data set

Returns
Number of columns in the input data set

Implements InputIface.

DAAL_EXPORT services::Status initialize ( const daal::algorithms::Input *  input,
const daal::algorithms::Parameter *  parameter,
const int  method 
)

Initializes memory to store a partial result of ridge regression model-based training

Parameters
[in]inputInput object for the algorithm
[in]methodMethod of ridge regression model-based training
[in]parameterParameter of ridge regression model-based training
Returns
Status of initialization
Input ( )

Default constructor

void set ( InputId  id,
const data_management::NumericTablePtr &  value 
)

Sets an input object for ridge regression model-based training

Parameters
[in]idIdentifier of the input object
[in]valuePointer to the object
void set ( PartialResultID  id,
const daal::algorithms::ridge_regression::ModelPtr &  value 
)

Sets an argument of the partial result

Parameters
[in]idIdentifier of the argument
[in]valuePointer to the argument
void set ( Step2MasterInputId  id,
const data_management::DataCollectionPtr &  ptr 
)

Sets an input object for ridge regression model-based training in the second step of the distributed processing mode

Parameters
[in]idIdentifier of the input object
[in]ptrInput object
void set ( ResultId  id,
const ridge_regression::ModelPtr &  value 
)

Sets the result of ridge regression model-based training

Parameters
[in]idIdentifier of the result
[in]valueResult

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