| Package | Description |
|---|---|
| org.drip.learning.rxtor1 |
| Class and Description |
|---|
| EmpiricalLearningMetricEstimator
EmpiricalLearningMetricEstimator is the Estimator of the Empirical Loss and Risk, as well as the
corresponding Covering Numbers.
|
| EmpiricalPenaltySupremum
EmpiricalPenaltySupremum holds the Learning Function that corresponds to the Empirical Supremum, as well
as the corresponding Supremum Value.
|
| EmpiricalPenaltySupremumEstimator
EmpiricalPenaltySupremumEstimator contains the Implementation of the Empirical Penalty Supremum Estimator
dependent on Multivariate Random Variables where the Multivariate Function is a Linear Combination of
Bounded Univariate Functions acting on each Random Variate.
|
| GeneralizedLearner
GeneralizedLearner implements the Learner Class that holds the Space of Normed R^x To Normed R^1 Learning
Functions along with their Custom Empirical Loss.
|
| LipschitzLossLearner
LipschitzLossLearner implements the Learner Class that holds the Space of Normed R^1 To Normed R^1
Learning Functions for the Family of Loss Functions that are Lipschitz, i.e.,
loss (ep) - loss (ep') Less Than C * |ep-ep'|
The References are:
1) Alon, N., S.
|