C++ API Reference for Intel® Data Analytics Acceleration Library 2018 Update 1

gbt_regression_training_batch.h
1 /* file: gbt_regression_training_batch.h */
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41 
42 /*
43 //++
44 // Implementation of the interface for model-based training
45 // in the batch processing mode
46 //--
47 */
48 
49 #ifndef __GBT_REGRESSSION_TRAINING_BATCH_H__
50 #define __GBT_REGRESSSION_TRAINING_BATCH_H__
51 
52 #include "algorithms/algorithm.h"
53 #include "data_management/data/numeric_table.h"
54 #include "services/daal_defines.h"
55 #include "services/daal_memory.h"
56 #include "algorithms/gradient_boosted_trees/gbt_regression_training_types.h"
57 #include "algorithms/gradient_boosted_trees/gbt_regression_model.h"
58 #include "algorithms/regression/regression_training_batch.h"
59 
60 namespace daal
61 {
62 namespace algorithms
63 {
64 namespace gbt
65 {
66 namespace regression
67 {
68 namespace training
69 {
70 namespace interface1
71 {
82 template<typename algorithmFPType, Method method, CpuType cpu>
83 class DAAL_EXPORT BatchContainer : public TrainingContainerIface<batch>
84 {
85 public:
91  BatchContainer(daal::services::Environment::env *daalEnv);
93  ~BatchContainer();
98  services::Status compute() DAAL_C11_OVERRIDE;
99 };
100 
116 template<typename algorithmFPType = DAAL_ALGORITHM_FP_TYPE, Method method = defaultDense>
117 class DAAL_EXPORT Batch : public algorithms::regression::training::Batch
118 {
119 public:
120  Input input;
123  Batch()
124  {
125  _par = new Parameter();
126  initialize();
127  }
128 
135  Batch(const Batch<algorithmFPType, method> &other) : input(other.input)
136  {
137  _par = new Parameter(other.parameter());
138  initialize();
139  }
140 
142  ~Batch()
143  {
144  delete _par;
145  }
146 
151  Parameter& parameter() { return *static_cast<Parameter*>(_par); }
152 
157  const Parameter& parameter() const { return *static_cast<const Parameter*>(_par); }
158 
163  virtual algorithms::regression::training::Input* getInput() DAAL_C11_OVERRIDE{ return &input; }
164 
169  virtual int getMethod() const DAAL_C11_OVERRIDE { return(int)method; }
170 
175  ResultPtr getResult() { return Result::cast(_result); }
176 
183  services::SharedPtr<Batch<algorithmFPType, method> > clone() const
184  {
185  return services::SharedPtr<Batch<algorithmFPType, method> >(cloneImpl());
186  }
187 
188 protected:
189 
190  virtual Batch<algorithmFPType, method> * cloneImpl() const DAAL_C11_OVERRIDE
191  {
192  return new Batch<algorithmFPType, method>(*this);
193  }
194 
195  services::Status allocateResult() DAAL_C11_OVERRIDE
196  {
197  services::Status s = getResult()->template allocate<algorithmFPType>(&input, &parameter(), method);
198  _res = _result.get();
199  return s;
200  }
201 
202  void initialize()
203  {
204  _ac = new __DAAL_ALGORITHM_CONTAINER(batch, BatchContainer, algorithmFPType, method)(&_env);
205  _in = &input;
206  _result.reset(new Result());
207  }
208 };
210 } // namespace interface1
211 using interface1::BatchContainer;
212 using interface1::Batch;
213 }
214 }
215 }
216 }
217 }
218 #endif
daal::algorithms::gbt::regression::training::interface1::Batch::getResult
ResultPtr getResult()
Definition: gbt_regression_training_batch.h:175
daal::algorithms::gbt::regression::training::interface1::Batch::~Batch
~Batch()
Definition: gbt_regression_training_batch.h:142
daal
Definition: algorithm_base_common.h:57
daal::algorithms::gbt::regression::training::interface1::Batch::getInput
virtual algorithms::regression::training::Input * getInput() DAAL_C11_OVERRIDE
Definition: gbt_regression_training_batch.h:163
daal_defines.h
daal::algorithms::gbt::regression::training::interface1::Batch::Batch
Batch(const Batch< algorithmFPType, method > &other)
Definition: gbt_regression_training_batch.h:135
daal::algorithms::gbt::regression::training::interface1::Batch::clone
services::SharedPtr< Batch< algorithmFPType, method > > clone() const
Definition: gbt_regression_training_batch.h:183
daal::algorithms::gbt::regression::training::interface1::BatchContainer
Class containing methods for gradient boosted trees regression model-based training using algorithmFP...
Definition: gbt_regression_training_batch.h:83
daal::batch
Definition: daal_defines.h:131
daal::algorithms::gbt::regression::training::interface1::Batch::getMethod
virtual int getMethod() const DAAL_C11_OVERRIDE
Definition: gbt_regression_training_batch.h:169
daal::algorithms::gbt::regression::training::interface1::Input
Input objects for model-based training
Definition: gbt_regression_training_types.h:149
daal::algorithms::gbt::regression::training::interface1::Batch
Provides methods for model-based training in the batch processing mode.
Definition: gbt_regression_training_batch.h:117
daal::algorithms::gbt::regression::training::interface1::Batch::Batch
Batch()
Definition: gbt_regression_training_batch.h:123
daal::algorithms::gbt::regression::training::interface1::Parameter
Parameters for the gradient boosted trees algorithm.
Definition: gbt_regression_training_types.h:135
daal::algorithms::gbt::regression::training::interface1::Batch::parameter
Parameter & parameter()
Definition: gbt_regression_training_batch.h:151
daal::algorithms::gbt::regression::training::interface1::Batch::parameter
const Parameter & parameter() const
Definition: gbt_regression_training_batch.h:157
daal::algorithms::gbt::regression::training::interface1::Batch::input
Input input
Definition: gbt_regression_training_batch.h:120
daal::algorithms::TrainingContainerIface
Abstract interface class that provides virtual methods to access and run implementations of the model...
Definition: training.h:76

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