Parameter of the iterative solver algorithm.
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◆ Parameter() [1/2]
Constructs the parameter for the iterative solver algorithm
- Parameters
-
context | Context to manage the parameter for the iterative solver algorithm |
◆ Parameter() [2/2]
Constructs the parameter for the iterative solver algorithm
- Parameters
-
context | Context to manage the iterative solver algorithm |
cObject | Pointer to C++ implementation of the parameter |
◆ getAccuracyThreshold()
double getAccuracyThreshold |
( |
| ) |
|
Gets the accuracy of the algorithm. The algorithm terminates when this accuracy is achieved
- Returns
- The accuracy of the algorithm. The algorithm terminates when this accuracy is achieved
◆ getBatchSize()
Returns the number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided.
- Returns
- The number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided.
◆ getFunction()
Gets objective function represented as sum of functions
- Returns
- Objective function represented as sum of functions
◆ getNIterations()
Gets the maximal number of iterations of the algorithm
- Returns
- The maximal number of iterations of the algorithm
◆ getOptionalResultRequired()
boolean getOptionalResultRequired |
( |
| ) |
|
Gets the optionalResultRequired flag
- Returns
- The flag
◆ setAccuracyThreshold()
void setAccuracyThreshold |
( |
double |
accuracyThreshold | ) |
|
Sets the accuracy of the algorithm. The algorithm terminates when this accuracy is achieved
- Parameters
-
accuracyThreshold | The accuracy of the algorithm. The algorithm terminates when this accuracy is achieved |
◆ setBatchSize()
void setBatchSize |
( |
long |
batchSize | ) |
|
Sets the number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided.
- Parameters
-
batchSize | The number of batch indices to compute the stochastic gradient. If batchSize is equal to the number of terms in objective function then no random sampling is performed, and all terms are used to calculate the gradient. This parameter is ignored if batchIndices is provided. |
◆ setFunction()
void setFunction |
( |
Batch |
function | ) |
|
Sets objective function represented as sum of functions
- Parameters
-
function | Objective function represented as sum of functions |
◆ setNIterations()
void setNIterations |
( |
long |
nIterations | ) |
|
Sets the maximal number of iterations of the algorithm
- Parameters
-
nIterations | The maximal number of iterations of the algorithm |
◆ setOptionalResultRequired()
void setOptionalResultRequired |
( |
boolean |
flag | ) |
|
Sets the optionalResultRequired flag
- Parameters
-
flag | The flag. If true, optional result is calculated |
The documentation for this class was generated from the following file:
- optimization_solver/iterative_solver/Parameter.java