Package | Description |
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org.drip.learning.bound | |
org.drip.learning.rxtor1 |
Modifier and Type | Method and Description |
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static CoveringNumberLossBound |
CoveringNumberBoundBuilder.AgnosticConvexLearning(R1ToR1 funcSampleCoefficient,
double dblExponentScaler)
Construct the Agnostic Convex Learning CoveringNumberProbabilityBound Instance
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static CoveringNumberLossBound |
CoveringNumberBoundBuilder.AgnosticLearning(R1ToR1 funcSampleCoefficient,
double dblExponentScaler)
Construct the Agnostic Learning CoveringNumberProbabilityBound Instance
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static CoveringNumberLossBound |
CoveringNumberBoundBuilder.RegressionLearning(R1ToR1 funcSampleCoefficient,
double dblExponentScaler)
Construct the Regression Learning CoveringNumberProbabilityBound Instance
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Modifier and Type | Method and Description |
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CoveringNumberLossBound |
GeneralizedLearner.coveringLossBoundEvaluator()
Retrieve the Covering Number based Deviation Upper Probability Bound Generator
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Constructor and Description |
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ApproximateLipschitzLossLearner(NormedRxToNormedR1Finite funcClassRxToR1,
CoveringNumberLossBound cdpb,
RegularizationFunction regularizerFunc,
double dblLipschitzSlope,
double dblLipschitzFloor)
ApproximateLipschitzLossLearner Constructor
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GeneralizedLearner(NormedRxToNormedR1Finite funcClassRxToR1,
CoveringNumberLossBound funcClassCNLB,
RegularizationFunction regularizerFunc)
GeneralizedLearner Constructor
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L1LossLearner(NormedRxToNormedR1Finite funcClassRxToR1,
CoveringNumberLossBound cdpb,
RegularizationFunction regularizerFunc,
MeasureConcentrationExpectationBound cleb)
L1LossLearner Constructor
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LipschitzLossLearner(NormedRxToNormedR1Finite funcClassRxToR1,
CoveringNumberLossBound cdpb,
RegularizationFunction regularizerFunc,
double dblLipschitzSlope)
LipschitzLossLearner Constructor
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LpLossLearner(NormedRxToNormedR1Finite funcClassRxToR1,
CoveringNumberLossBound cdpb,
RegularizationFunction regularizerFunc,
double dblLossExponent)
LpLossLearner Constructor
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