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