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

logistic_regression_model_builder.h
1 /* file: logistic_regression_model_builder.h */
2 /*******************************************************************************
3 * Copyright 2014-2020 Intel Corporation
4 *
5 * Licensed under the Apache License, Version 2.0 (the "License");
6 * you may not use this file except in compliance with the License.
7 * You may obtain a copy of the License at
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9 * http://www.apache.org/licenses/LICENSE-2.0
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14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 *******************************************************************************/
17 
18 /*
19 //++
20 // Implementation of the class defining the logistic regression model builder
21 //--
22 */
23 
24 #ifndef __LOGISTIC_REGRESSION_MODEL_BUILDER_H__
25 #define __LOGISTIC_REGRESSION_MODEL_BUILDER_H__
26 
27 #include "algorithms/logistic_regression/logistic_regression_model.h"
28 
29 namespace daal
30 {
31 namespace algorithms
32 {
41 namespace logistic_regression
42 {
46 namespace interface1
47 {
60 template<typename modelFPType = DAAL_ALGORITHM_FP_TYPE>
61 class DAAL_EXPORT ModelBuilder
62 {
63 public:
64 
70  ModelBuilder(size_t nFeatures, size_t nClasses);
71 
79  template<typename RandomIterator>
80  void setBeta(RandomIterator first, RandomIterator last)
81  {
82  data_management::BlockDescriptor<modelFPType> pBlock;
83  const size_t nVectorsBeta = _nClasses == 2 ? 1 : _nClasses;
84  _modelPtr->getBeta()->getBlockOfRows(0, nVectorsBeta, data_management::readWrite, pBlock);
85  modelFPType* sp = pBlock.getBlockPtr();
86  if((last - first) == _nFeatures*nVectorsBeta)
87  {
88  setInterceptFlag(false);
89  size_t i = 0;
90  while(first != last)
91  {
92  if((i % (_nFeatures + 1)) == 0)
93  {
94  sp[i] = 0;
95  ++i;
96  }
97  sp[i] = *first;
98  ++first;
99  ++i;
100  }
101  }
102  else if((last - first) == (_nFeatures + 1)*nVectorsBeta)
103  {
104  setInterceptFlag(true);
105  while(first != last)
106  {
107  *sp = *first;
108  ++first;
109  ++sp;
110  }
111  }
112  else
113  {
114  _s = services::Status(services::ErrorIncorrectParameter);
115  _modelPtr->getBeta()->releaseBlockOfRows(pBlock);
116  services::throwIfPossible(_s);
117  return;
118  }
119  _modelPtr->getBeta()->releaseBlockOfRows(pBlock);
120  }
121 
126  ModelPtr getModel()
127  {
128  return _modelPtr;
129  }
130 
135  services::Status getStatus()
136  {
137  return _s;
138  }
139 
140 private:
141  ModelPtr _modelPtr;
142  services::Status _s;
143  size_t _nFeatures;
144  size_t _nClasses;
145 
146  void setInterceptFlag(bool interceptFlag);
147 };
148 
150 } // namespace interface1
151 using interface1::ModelBuilder;
152 
153 } // namespace logistic_regression
154 } // namespace algorithms
155 } // namespace daal
156 #endif
daal::algorithms::logistic_regression::interface1::ModelBuilder::getStatus
services::Status getStatus()
Definition: logistic_regression_model_builder.h:135
daal::algorithms::logistic_regression::interface1::ModelBuilder
Class for building model of the logistic regression algorithm
Definition: logistic_regression_model_builder.h:61
daal::algorithms::logistic_regression::interface1::ModelBuilder::getModel
ModelPtr getModel()
Definition: logistic_regression_model_builder.h:126
daal::algorithms::logistic_regression::interface1::ModelBuilder::setBeta
void setBeta(RandomIterator first, RandomIterator last)
Definition: logistic_regression_model_builder.h:80
daal::services::ErrorIncorrectParameter
Definition: error_indexes.h:99

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