Python* API Reference for Intel® Data Analytics Acceleration Library 2019
Provides methods to train models that depend on the data provided. More...
Additional Inherited Members | |
Public Member Functions inherited from AlgorithmImpl | |
| def | computeNoThrow |
| def | compute |
| def | checkComputeParams |
| def | checkResult |
| def | setupCompute |
| def | resetCompute |
| def | enableResetOnCompute |
| def | hostApp |
| def | setHostApp |
Public Member Functions inherited from Algorithm | |
| def | checkComputeParams |
| def | getBaseParameter |
Public Member Functions inherited from AlgorithmIfaceImpl | |
| def | enableChecks |
| def | isChecksEnabled |
| def | getErrors |
Public Member Functions inherited from AlgorithmIface | |
| def | checkComputeParams |
| def | checkResult |
| def | getMethod |
| def | getErrors |
For example, these methods enable training the linear regression model. The methods of the class support different computation modes: batch, distributed, and online(see ComputeMode). Classes that implement specific algorithms of model training are derived classes of the Training class. The class additionally provides methods for validation of input and output parameters of the algorithms.
| mode | Computation mode of the algorithm, ComputeMode |
Training_Batch is an alias of Training(cmode=daal.batch)Training_Online is an alias of Training(cmode=daal.online)Training_Distributed is an alias of Training(cmode=daal.distributed) For more complete information about compiler optimizations, see our Optimization Notice.