See: Description
Interface | Description |
---|---|
AnytimeBatchLearner<DataType,ResultType> |
A batch learner that is also and Anytime algorithm.
|
BatchAndIncrementalLearner<DataType,ResultType> |
Interface for an algorithm that is both a batch and incremental learner.
|
BatchCostMinimizationLearner<CostParametersType,ResultType> |
The
BatchCostMinimizationLearner interface defines the functionality
of a cost-minimization learning algorithm should follow. |
BatchLearner<DataType,ResultType> |
The
BatchLearner interface defines the general functionality
of an object that is the implementation of a data-driven, batch machine
learning algorithm. |
BatchLearnerContainer<LearnerType extends BatchLearner<?,?>> |
An interface for an object that contains a batch learner.
|
DimensionFilterableLearner |
Interface for a learner that can be filtered by which dimensions it
includes in learning.
|
IncrementalLearner<DataType,ResultType> |
The
IncrementalLearner interface defines the general functionality
of an object that is the implementation of a data-driven, incremental machine
learning algorithm. |
SupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> |
Interface for a class that is a supervised learning algorithm that can be
used both batch and incremental contexts.
|
SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> |
The
BatchSupervisedLearner interface is an extension of the
BatchLearner interface that contains the typical generic definition
conventions for a batch, supervised learning algorithm. |
SupervisedIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> |
Interface for supervised incremental learning algorithms.
|
Class | Description |
---|---|
AbstractAnytimeBatchLearner<DataType,ResultType> |
The
AbstractAnytimeBatchLearner abstract class
implements a standard method for conforming to the BatchLearner and
AnytimeLearner (IterativeAlgorithm and
StoppableAlgorithm ) interfaces. |
AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> |
The
AbstractAnytimeSupervisedBatchLearner abstract class extends
the AbstractAnytimeBatchLearner to implement the
SupervisedBatchLearner interface. |
AbstractBatchAndIncrementalLearner<DataType,ResultType> |
An abstract class that has both batch learning ability as well as online
learning ability by taking a Collection of input data.
|
AbstractBatchLearnerContainer<LearnerType extends BatchLearner<?,?>> |
An abstract class for objects that contain a batch learning algorithm.
|
AbstractSupervisedBatchAndIncrementalLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> |
An abstract implementation of the batch and incremental learning for
an incremental supervised learner.
|
CompositeBatchLearnerPair<InputType,IntermediateType,OutputType> |
Composes together a pair of batch (typically unsupervised) learners.
|
InputOutputTransformedBatchLearner<InputType,TransformedInputType,TransformedOutputType,OutputType> |
An adapter class for performing supervised learning from data where both
the input and output have to be transformed before they are passed to the
learning algorithm.
|
SequencePredictionLearner<DataType,LearnedType> |
A wrapper learner that converts an unlabeled sequence of data into a sequence
of prediction data using a fixed prediction horizon.
|
TimeSeriesPredictionLearner<InputType,OutputType,EvaluatorType extends Evaluator<? super InputType,? extends OutputType>> |
A learner used to predict the future of a sequence of data by wrapping
another learner and created a future-aligned data set.
|