C++ API Reference for Intel® Data Analytics Acceleration Library 2019 Update 5
BrownBoost algorithm parameters. More...
| Parameter | ( | ) |
Default constructor
| Parameter | ( | services::SharedPtr< weak_learner::training::Batch > | wlTrainForParameter, |
| services::SharedPtr< weak_learner::prediction::Batch > | wlPredictForParameter, | ||
| double | acc = 0.3, |
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| size_t | maxIter = 10, |
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| double | nrAcc = 1.0e-3, |
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| size_t | nrMaxIter = 100, |
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| double | dcThreshold = 1.0e-2 |
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| ) |
Constructs BrownBoost parameter structure
| [in] | wlTrainForParameter | Pointer to the training algorithm of the weak learner |
| [in] | wlPredictForParameter | Pointer to the prediction algorithm of the weak learner |
| [in] | acc | Accuracy of the BrownBoost training algorithm |
| [in] | maxIter | Maximal number of iterations of the BrownBoost training algorithm |
| [in] | nrAcc | Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm |
| [in] | nrMaxIter | Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm |
| [in] | dcThreshold | Threshold needed to avoid degenerate cases in the BrownBoost training algorithm |
| double accuracyThreshold |
Accuracy of the BrownBoost training algorithm
| double degenerateCasesThreshold |
Threshold needed to avoid degenerate cases in the BrownBoost training algorithm
| size_t maxIterations |
Maximal number of iterations of the BrownBoost training algorithm
| double newtonRaphsonAccuracyThreshold |
Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm
| size_t newtonRaphsonMaxIterations |
Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm
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