- Type Parameters:
InputType
- The type of input data in the input-output pair that
the learner can learn from. The Evaluator
learned from the
algorithm also takes this as the input parameter.
OutputType
- The type of output data in the input-output pair that
the learner can learn from. The Evaluator
learned from the
algorithm also produces this as its output.
ResultType
- The type of object created by the learning algorithm.
For example, a LinearBinaryCategorizer
.
- All Superinterfaces:
- BatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>, BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,ResultType>, java.lang.Cloneable, CloneableSerializable, IncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>, java.io.Serializable, SupervisedBatchLearner<InputType,OutputType,ResultType>, SupervisedIncrementalLearner<InputType,OutputType,ResultType>
- All Known Subinterfaces:
- KernelizableBinaryCategorizerOnlineLearner, LinearizableBinaryCategorizerOnlineLearner<InputType>
- All Known Implementing Classes:
- AbstractKernelizableBinaryCategorizerOnlineLearner, AbstractLinearCombinationOnlineLearner, AbstractOnlineBudgetedKernelBinaryCategorizerLearner, AbstractOnlineKernelBinaryCategorizerLearner, AbstractOnlineLinearBinaryCategorizerLearner, AbstractSupervisedBatchAndIncrementalLearner, AdaptiveRegularizationOfWeights, AggressiveRelaxedOnlineMaximumMarginAlgorithm, Ballseptron, ConfidenceWeightedDiagonalDeviation, ConfidenceWeightedDiagonalDeviationProject, ConfidenceWeightedDiagonalVariance, ConfidenceWeightedDiagonalVarianceProject, Forgetron, Forgetron.Basic, Forgetron.Greedy, KernelBinaryCategorizerOnlineLearnerAdapter, OnlineBaggingCategorizerLearner, OnlineBinaryMarginInfusedRelaxedAlgorithm, OnlineKernelPerceptron, OnlineKernelRandomizedBudgetPerceptron, OnlinePassiveAggressivePerceptron, OnlinePassiveAggressivePerceptron.AbstractSoftMargin, OnlinePassiveAggressivePerceptron.LinearSoftMargin, OnlinePassiveAggressivePerceptron.QuadraticSoftMargin, OnlinePerceptron, OnlineRampPassiveAggressivePerceptron, OnlineShiftingPerceptron, OnlineVotedPerceptron, Projectron, Projectron.LinearSoftMargin, RelaxedOnlineMaximumMarginAlgorithm, RemoveOldestKernelPerceptron, Stoptron, Winnow
public interface SupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>>
extends SupervisedIncrementalLearner<InputType,OutputType,ResultType>, SupervisedBatchLearner<InputType,OutputType,ResultType>, BatchAndIncrementalLearner<InputOutputPair<? extends InputType,OutputType>,ResultType>
Interface for a class that is a supervised learning algorithm that can be
used both batch and incremental contexts.
- Since:
- 3.2.0
- Author:
- Justin Basilico