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

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  services::Status setupCompute() DAAL_C11_OVERRIDE;
100 };
101 
117 template<typename algorithmFPType = DAAL_ALGORITHM_FP_TYPE, Method method = defaultDense>
118 class DAAL_EXPORT Batch : public algorithms::regression::training::Batch
119 {
120 public:
121  typedef algorithms::gbt::regression::training::Input InputType;
122  typedef algorithms::gbt::regression::training::Parameter ParameterType;
123  typedef algorithms::gbt::regression::training::Result ResultType;
124 
125  InputType input;
128  Batch()
129  {
130  _par = new ParameterType();
131  initialize();
132  }
133 
140  Batch(const Batch<algorithmFPType, method> &other) : input(other.input)
141  {
142  _par = new ParameterType(other.parameter());
143  initialize();
144  }
145 
147  ~Batch()
148  {
149  delete _par;
150  }
151 
156  ParameterType& parameter() { return *static_cast<ParameterType*>(_par); }
157 
162  const ParameterType& parameter() const { return *static_cast<const ParameterType*>(_par); }
163 
168  virtual algorithms::regression::training::Input* getInput() DAAL_C11_OVERRIDE{ return &input; }
169 
174  virtual int getMethod() const DAAL_C11_OVERRIDE { return(int)method; }
175 
180  ResultPtr getResult() { return ResultType::cast(_result); }
181 
188  services::SharedPtr<Batch<algorithmFPType, method> > clone() const
189  {
190  return services::SharedPtr<Batch<algorithmFPType, method> >(cloneImpl());
191  }
192 
193 protected:
194 
195  virtual Batch<algorithmFPType, method> * cloneImpl() const DAAL_C11_OVERRIDE
196  {
197  return new Batch<algorithmFPType, method>(*this);
198  }
199 
200  services::Status allocateResult() DAAL_C11_OVERRIDE
201  {
202  services::Status s = getResult()->template allocate<algorithmFPType>(&input, &parameter(), method);
203  _res = _result.get();
204  return s;
205  }
206 
207  void initialize()
208  {
209  _ac = new __DAAL_ALGORITHM_CONTAINER(batch, BatchContainer, algorithmFPType, method)(&_env);
210  _in = &input;
211  _result.reset(new ResultType());
212  }
213 };
215 } // namespace interface1
216 using interface1::BatchContainer;
217 using interface1::Batch;
218 }
219 }
220 }
221 }
222 }
223 #endif
daal::algorithms::regression::training::interface1::Input
Input objects for the regression model-based training
Definition: regression_training_types.h:102
daal::algorithms::gbt::regression::training::interface1::Batch::getResult
ResultPtr getResult()
Definition: gbt_regression_training_batch.h:180
daal::algorithms::gbt::regression::training::interface1::Batch::~Batch
~Batch()
Definition: gbt_regression_training_batch.h:147
daal::services::interface1::Environment::_envStruct
The environment structure.
Definition: env_detect.h:95
daal::services::interface1::Status
Class that holds the results of API calls. In case of API routine failure it contains the list of err...
Definition: error_handling.h:491
daal
Definition: algorithm_base_common.h:57
daal::algorithms::gbt::regression::training::interface1::Result
Provides methods to access the result obtained with the compute() method of model-based training...
Definition: gbt_regression_training_types.h:188
daal::algorithms::gbt::regression::training::interface1::Batch::getInput
virtual algorithms::regression::training::Input * getInput() DAAL_C11_OVERRIDE
Definition: gbt_regression_training_batch.h:168
daal_defines.h
daal::algorithms::gbt::regression::training::interface1::Batch::Batch
Batch(const Batch< algorithmFPType, method > &other)
Definition: gbt_regression_training_batch.h:140
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:132
daal::services::interface1::SharedPtr
Shared pointer that retains shared ownership of an object through a pointer. Several SharedPtr object...
Definition: daal_shared_ptr.h:187
daal::algorithms::gbt::regression::training::interface1::Batch::getMethod
virtual int getMethod() const DAAL_C11_OVERRIDE
Definition: gbt_regression_training_batch.h:174
daal::algorithms::regression::training::interface1::Batch
Provides methods for the regression model-based training in the batch processing mode.
Definition: regression_training_batch.h:77
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::input
InputType input
Definition: gbt_regression_training_batch.h:125
daal::algorithms::gbt::regression::training::interface1::Batch::parameter
const ParameterType & parameter() const
Definition: gbt_regression_training_batch.h:162
daal::algorithms::gbt::regression::training::interface1::Batch::parameter
ParameterType & parameter()
Definition: gbt_regression_training_batch.h:156
daal::algorithms::gbt::regression::training::interface1::Batch
Provides methods for model-based training in the batch processing mode.
Definition: gbt_regression_training_batch.h:118
daal::algorithms::gbt::regression::training::interface1::Batch::Batch
Batch()
Definition: gbt_regression_training_batch.h:128
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::clone
services::SharedPtr< Batch< algorithmFPType, method > > clone() const
Definition: gbt_regression_training_batch.h:188
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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