Contains a class for lasso regression model-based training.
More...
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| struct | Parameter |
| | Parameters for the lasso regression algorithm. More...
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| class | InputIface |
| | Abstract class that specifies the interface of input objects for lasso regression model-based training. More...
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| class | Input |
| | Input objects for lasso regression model-based training More...
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| class | Result |
| | Provides methods to access the result obtained with the compute() method of lasso regression model-based training. More...
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| virtual size_t | getNumberOfFeatures () const =0 |
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| virtual size_t | getNumberOfDependentVariables () const =0 |
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| | Input () |
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| data_management::NumericTablePtr | get (InputId id) const |
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| void | set (InputId id, const data_management::NumericTablePtr &value) |
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| algorithms::OptionalArgumentPtr | get (OptionalInputId id) const |
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| void | set (OptionalInputId id, const algorithms::OptionalArgumentPtr &ptr) |
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| data_management::NumericTablePtr | get (OptionalDataId id) const |
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| void | set (OptionalDataId id, const data_management::NumericTablePtr &ptr) |
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| size_t | getNumberOfFeatures () const DAAL_C11_OVERRIDE |
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| size_t | getNumberOfDependentVariables () const DAAL_C11_OVERRIDE |
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| services::Status | check (const daal::algorithms::Parameter *par, int method) const DAAL_C11_OVERRIDE |
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| lasso_regression::ModelPtr | get (ResultId id) const |
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| void | set (ResultId id, const lasso_regression::ModelPtr &value) |
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| data_management::NumericTablePtr | get (OptionalResultNumericTableId id) const |
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| void | set (OptionalResultNumericTableId id, const data_management::NumericTablePtr &value) |
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| template<typename algorithmFPType > |
| DAAL_EXPORT services::Status | allocate (const daal::algorithms::Input *input, const Parameter *parameter, const int method) |
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| services::Status | check (const daal::algorithms::Input *input, const daal::algorithms::Parameter *par, int method) const DAAL_C11_OVERRIDE |
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| enum DataUseInComputation |
| Enumerator |
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| doNotUse |
The input data and labels can`t be corrupted
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| doUse |
The input data and labels can be corrupted
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| Enumerator |
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| data |
Input data table
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| dependentVariables |
Values of the dependent variable for the input data
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| Enumerator |
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| defaultDense |
Normal equations method
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Available identifiers of optional input for the iterative solver
| Enumerator |
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| weights |
NumericTable of size 1 x n with weights of samples. Applied for all method
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| gramMatrix |
NumericTable of size p x p with last iteration number. Applied for all method
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Available identifiers of optional input for the iterative solver
| Enumerator |
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| optionalArgument |
Algorithm-specific input data, can be generated by previous runs of the algorithm
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| enum OptionalResultNumericTableId |
Available identifiers of results obtained in the training stage of the regression algorithm
| Enumerator |
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| gramMatrixId |
Numeric table of size: p x p, containing computed Gram matrix
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| Enumerator |
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| model |
Lasso regression model
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Available identifiers to specify the result to compute
| Enumerator |
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| computeGramMatrix |
The flag to compute Gram Matrix
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| DAAL_EXPORT services::Status allocate |
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const daal::algorithms::Input * |
input, |
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const Parameter * |
parameter, |
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const int |
method |
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) |
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Allocates memory to store the result of lasso regression model-based training
- Parameters
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| [in] | input | Pointer to an object containing the input data |
| [in] | parameter | Parameter of lasso regression model-based training |
| [in] | method | Computation method for the algorithm |
- Returns
- Status of computations
| services::Status check |
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const daal::algorithms::Parameter * |
par, |
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int |
method |
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) |
| const |
Checks an input object for the lasso regression algorithm
- Parameters
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| [in] | par | Algorithm parameter |
| [in] | method | Computation method |
- Returns
- Status of computations
| services::Status check |
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const daal::algorithms::Input * |
input, |
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const daal::algorithms::Parameter * |
par, |
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int |
method |
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) |
| const |
Checks the result of lasso regression model-based training
- Parameters
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| [in] | input | Input object for the algorithm |
| [in] | par | Parameter of the algorithm |
| [in] | method | Computation method |
- Returns
- Status of computations
| data_management::NumericTablePtr get |
( |
InputId |
id | ) |
const |
Returns an input object for lasso regression model-based training
- Parameters
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| [in] | id | Identifier of the input object |
- Returns
- Input object that corresponds to the given identifier
Returns optional input of the iterative solver algorithm
- Parameters
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| [in] | id | Identifier of the optional input data |
- Returns
- Input data that corresponds to the given identifier
Returns input NumericTable containing optional data
- Parameters
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| [in] | id | Identifier of the input numeric table |
- Returns
- Input numeric table that corresponds to the given identifier
| lasso_regression::ModelPtr get |
( |
ResultId |
id | ) |
const |
Returns the result of lasso regression model-based training
- Parameters
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| [in] | id | Identifier of the result |
- Returns
- Result that corresponds to the given identifier
Returns the result of lasso regression model-based training
- Parameters
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| [in] | id | Identifier of the result |
- Returns
- Result that corresponds to the given identifier
| virtual size_t getNumberOfDependentVariables |
( |
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const |
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pure virtual |
Returns the number of dependent variables
- Returns
- Number of dependent variables
Implemented in Input.
| size_t getNumberOfDependentVariables |
( |
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const |
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virtual |
Returns the number of dependent variables
- Returns
- Number of dependent variables
Implements InputIface.
| virtual size_t getNumberOfFeatures |
( |
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const |
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pure virtual |
Returns the number of columns in the input data set
- Returns
- Number of columns in the input data set
Implemented in Input.
| size_t getNumberOfFeatures |
( |
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const |
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virtual |
Returns the number of columns in the input data set
- Returns
- Number of columns in the input data set
Implements InputIface.
| void set |
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InputId |
id, |
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const data_management::NumericTablePtr & |
value |
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) |
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Sets an input object for lasso regression model-based training
- Parameters
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| [in] | id | Identifier of the input object |
| [in] | value | Pointer to the object |
| void set |
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OptionalInputId |
id, |
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const algorithms::OptionalArgumentPtr & |
ptr |
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) |
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Sets optional input for the iterative solver algorithm
- Parameters
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| [in] | id | Identifier of the input object |
| [in] | ptr | Pointer to the object |
| void set |
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OptionalDataId |
id, |
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const data_management::NumericTablePtr & |
ptr |
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) |
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Sets optional input for the algorithm
- Parameters
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| [in] | id | Identifier of the input object |
| [in] | ptr | Pointer to the object |
| void set |
( |
ResultId |
id, |
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const lasso_regression::ModelPtr & |
value |
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) |
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Sets the result of lasso regression model-based training
- Parameters
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| [in] | id | Identifier of the result |
| [in] | value | Result |
Sets the result of lasso regression model-based training
- Parameters
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| [in] | id | Identifier of the input object |
| [in] | value | Input object |
| DataUseInComputation dataUseInComputation |
The flag allows to corrupt input data
| data_management::NumericTablePtr lassoParameters |
Numeric table that contains values of lasso parameters
| SolverPtr optimizationSolver |
Default is coordinate descent solver
| DAAL_UINT64 optResultToCompute |
64 bit integer flag that indicates the optional results to compute