C++ API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5
Contains version 1.0 of the Intel(R) Data Analytics Acceleration Library (Intel(R) DAAL) interface.
Classes | |
| class | Batch |
| Algorithm class for training the implicit ALS model. More... | |
| class | BatchContainer |
| Provides methods to run implementations of implicit ALS model-based training. More... | |
| class | Distributed |
| Trains the implicit ALS model in the distributed processing mode. More... | |
| class | Distributed< step1Local, algorithmFPType, method > |
| Trains the implicit ALS model in the first step of the distributed processing mode. More... | |
| class | Distributed< step2Master, algorithmFPType, method > |
| Trains the implicit ALS model in the second step of the distributed processing mode. More... | |
| class | Distributed< step3Local, algorithmFPType, method > |
| Trains the implicit ALS model in the third step of the distributed processing mode. More... | |
| class | Distributed< step4Local, algorithmFPType, method > |
| Trains the implicit ALS model in the fourth step of the distributed processing mode. More... | |
| class | DistributedContainer |
| Class containing methods to compute the result of implicit ALS model-based training in the distributed processing mode. More... | |
| class | DistributedContainer< step1Local, algorithmFPType, method, cpu > |
| Class containing methods to train the implicit ALS model in the first step of the distributed processing mode. More... | |
| class | DistributedContainer< step2Master, algorithmFPType, method, cpu > |
| Class containing methods to train the implicit ALS model in the second step of the distributed processing mode. More... | |
| class | DistributedContainer< step3Local, algorithmFPType, method, cpu > |
| Class containing methods to train the implicit ALS model in the third step of the distributed processing mode. More... | |
| class | DistributedContainer< step4Local, algorithmFPType, method, cpu > |
| Class containing methods to train the implicit ALS model in the fourth step of the distributed processing mode. More... | |
| class | DistributedInput |
| Input objects for the implicit ALS training algorithm in the distributed processing mode More... | |
| class | DistributedInput< step1Local > |
| Input objects for the implicit ALS training algorithm in the first step of the distributed processing mode More... | |
| class | DistributedInput< step2Master > |
| Input objects for the implicit ALS training algorithm in the second step of the distributed processing mode More... | |
| class | DistributedInput< step3Local > |
| Input objects for the implicit ALS training algorithm in the third step of the distributed processing mode More... | |
| class | DistributedInput< step4Local > |
| Input objects for the implicit ALS training algorithm in the fourth step of the distributed processing mode More... | |
| class | DistributedPartialResultStep1 |
| Provides methods to access partial results obtained with the compute() method of the implicit ALS algorithm in the first step of the distributed processing mode. More... | |
| class | DistributedPartialResultStep2 |
| Provides methods to access partial results obtained with the compute() method of the implicit ALS algorithm in the second step of the distributed processing mode. More... | |
| class | DistributedPartialResultStep3 |
| Provides methods to access partial results obtained with the compute() method of the implicit ALS algorithm in the the third step of the distributed processing mode. More... | |
| class | DistributedPartialResultStep4 |
| Provides methods to access partial results obtained with the compute() method of the implicit ALS algorithm in the the fourth step of the distributed processing mode. More... | |
| class | Input |
| Input objects for the implicit ALS training algorithm More... | |
| class | Result |
| Provides methods to access the results obtained with the compute() method of the implicit ALS training algorithm in the batch processing mode. More... | |
For more complete information about compiler optimizations, see our Optimization Notice.