BrownBoost algorithm parameters.
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def __init__ |
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- Variant 1
- Default constructor
- Variant 2
Constructs BrownBoost parameter structure
- Parameters
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wlTrainForParameter | Pointer to the training algorithm of the weak learner |
wlPredictForParameter | Pointer to the prediction algorithm of the weak learner |
acc | Accuracy of the BrownBoost training algorithm |
maxIter | Maximal number of iterations of the BrownBoost training algorithm |
nrAcc | Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm |
nrMaxIter | Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm |
dcThreshold | Threshold needed to avoid degenerate cases in the BrownBoost training algorithm |
- Variant 3
Constructs BrownBoost parameter structure
- Parameters
-
wlTrainForParameter | Pointer to the training algorithm of the weak learner |
wlPredictForParameter | Pointer to the prediction algorithm of the weak learner |
acc | Accuracy of the BrownBoost training algorithm |
maxIter | Maximal number of iterations of the BrownBoost training algorithm |
nrAcc | Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm |
nrMaxIter | Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm |
dcThreshold | Threshold needed to avoid degenerate cases in the BrownBoost training algorithm |
- Variant 4
Constructs BrownBoost parameter structure
- Parameters
-
wlTrainForParameter | Pointer to the training algorithm of the weak learner |
wlPredictForParameter | Pointer to the prediction algorithm of the weak learner |
acc | Accuracy of the BrownBoost training algorithm |
maxIter | Maximal number of iterations of the BrownBoost training algorithm |
nrAcc | Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm |
nrMaxIter | Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm |
dcThreshold | Threshold needed to avoid degenerate cases in the BrownBoost training algorithm |
- Variant 5
Constructs BrownBoost parameter structure
- Parameters
-
wlTrainForParameter | Pointer to the training algorithm of the weak learner |
wlPredictForParameter | Pointer to the prediction algorithm of the weak learner |
acc | Accuracy of the BrownBoost training algorithm |
maxIter | Maximal number of iterations of the BrownBoost training algorithm |
nrAcc | Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm |
nrMaxIter | Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm |
dcThreshold | Threshold needed to avoid degenerate cases in the BrownBoost training algorithm |
- Variant 6
Constructs BrownBoost parameter structure
- Parameters
-
wlTrainForParameter | Pointer to the training algorithm of the weak learner |
wlPredictForParameter | Pointer to the prediction algorithm of the weak learner |
acc | Accuracy of the BrownBoost training algorithm |
maxIter | Maximal number of iterations of the BrownBoost training algorithm |
nrAcc | Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm |
nrMaxIter | Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm |
dcThreshold | Threshold needed to avoid degenerate cases in the BrownBoost training algorithm |
- Variant 7
Constructs BrownBoost parameter structure
- Parameters
-
wlTrainForParameter | Pointer to the training algorithm of the weak learner |
wlPredictForParameter | Pointer to the prediction algorithm of the weak learner |
acc | Accuracy of the BrownBoost training algorithm |
maxIter | Maximal number of iterations of the BrownBoost training algorithm |
nrAcc | Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm |
nrMaxIter | Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm |
dcThreshold | Threshold needed to avoid degenerate cases in the BrownBoost training algorithm |
check(interface2_Parameter self) -> Status
Accuracy of the BrownBoost training algorithm
degenerateCasesThreshold = ... |
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Threshold needed to avoid degenerate cases in the BrownBoost training algorithm
Maximal number of iterations of the BrownBoost training algorithm
newtonRaphsonAccuracyThreshold = ... |
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Accuracy threshold for Newton-Raphson iterations in the BrownBoost training algorithm
newtonRaphsonMaxIterations = ... |
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Maximal number of Newton-Raphson iterations in the BrownBoost training algorithm
weakLearnerPrediction = ... |
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The algorithm for prediction based on a weak learner model
weakLearnerTraining = ... |
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The algorithm for weak learner model training
The documentation for this class was generated from the following file:
- algorithms/brownboost/__init__.py