C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 2

References | Namespaces | Classes | Enumerations | Enumerator | 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

◆ InputId

enum InputId

Enumerator
data 

Input data table

dependentVariables 

Values of the dependent variable for the input data

◆ Method

enum Method

Enumerator
defaultDense 

Normal equations method

normEqDense 

Normal equations method

◆ PartialResultID

Enumerator
partialModel 

Partial model trained on the available input data

◆ ResultId

enum ResultId

Enumerator
model 

Linear regression model

◆ Step2MasterInputId

Enumerator
partialModels 

Collection of partial models trained on local nodes

Function Documentation

◆ add()

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

◆ allocate() [1/3]

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

◆ allocate() [2/3]

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

◆ allocate() [3/3]

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

◆ check() [1/6]

services::Status check ( const daal::algorithms::Parameter par,
int  method 
) const
virtual

Checks an input object for the ridge regression algorithm

Parameters
[in]parAlgorithm parameter
[in]methodComputation method
Returns
Status of computations

Reimplemented from Input.

◆ check() [2/6]

services::Status check ( const daal::algorithms::Input input,
const daal::algorithms::Parameter par,
int  method 
) const
virtual

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

Reimplemented from PartialResult.

◆ check() [3/6]

services::Status check ( const daal::algorithms::Parameter par,
int  method 
) const
virtual

Checks a partial result of the ridge regression algorithm

Parameters
[in]parParameter of the algorithm
[in]methodComputation method
Returns
Status of computations

Reimplemented from PartialResult.

◆ check() [4/6]

services::Status check ( const daal::algorithms::Parameter parameter,
int  method 
) const
virtual

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

Returns
Status of computations

Reimplemented from Input.

◆ check() [5/6]

services::Status check ( const daal::algorithms::Input input,
const daal::algorithms::Parameter par,
int  method 
) const
virtual

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

Reimplemented from Result.

◆ check() [6/6]

services::Status check ( const daal::algorithms::PartialResult pr,
const daal::algorithms::Parameter par,
int  method 
) const
virtual

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

Reimplemented from Result.

◆ get() [1/4]

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

◆ get() [2/4]

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

◆ get() [3/4]

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

◆ get() [4/4]

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

◆ getNumberOfDependentVariables() [1/4]

virtual size_t getNumberOfDependentVariables ( ) const
pure virtual

Returns the number of dependent variables

Returns
Number of dependent variables

Implemented in DistributedInput< step2Master >, and Input.

◆ getNumberOfDependentVariables() [2/4]

size_t getNumberOfDependentVariables ( ) const
virtual

Returns the number of dependent variables

Returns
Number of dependent variables

Implements InputIface.

◆ getNumberOfDependentVariables() [3/4]

size_t getNumberOfDependentVariables ( ) const

Returns the number of dependent variables

Returns
Number of dependent variables

◆ getNumberOfDependentVariables() [4/4]

size_t getNumberOfDependentVariables ( ) const
virtual

Returns the number of dependent variables

Returns
Number of dependent variables

Implements InputIface.

◆ getNumberOfFeatures() [1/4]

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.

◆ getNumberOfFeatures() [2/4]

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.

◆ getNumberOfFeatures() [3/4]

size_t getNumberOfFeatures ( ) const

Returns the number of columns in the input data set

Returns
Number of columns in the input data set

◆ getNumberOfFeatures() [4/4]

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.

◆ initialize()

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()

Input ( )

Default constructor

◆ set() [1/4]

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

◆ set() [2/4]

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

◆ set() [3/4]

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

◆ set() [4/4]

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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