DataType
- Data used to train the ResultType
.ResultType
- The type of object created and modified by the
learning algorithm. For example, a FeedforwardNeuralNetwork
.@CodeReview(reviewer="Kevin R. Dixon", date="2008-07-22", changesNeeded=false, comments={"Fixed a couple of javadoc typos.","Interface looks fine."}) public interface IncrementalLearner<DataType,ResultType> extends CloneableSerializable
IncrementalLearner
interface defines the general functionality
of an object that is the implementation of a data-driven, incremental machine
learning algorithm. It is the analog of the BatchLearner
interface but for incremental learning.
IncrementalLearner
object (usually as a Java Bean) and then the data
is passed in using the learn method to create the result object of the
learning algorithm.
ResultType
using the new given data.
BatchLearner
Modifier and Type | Method and Description |
---|---|
ResultType |
createInitialLearnedObject()
Creates a new initial learned object, before any data is given.
|
void |
update(ResultType target,
DataType data)
The
update method updates an object of ResultType using
the given new data of type DataType , using some form of
"learning" algorithm. |
void |
update(ResultType target,
java.lang.Iterable<? extends DataType> data)
The
update method updates an object of ResultType using
the given new Iterable containing some number of type DataType ,
using some form of "learning" algorithm. |
clone
ResultType createInitialLearnedObject()
void update(ResultType target, DataType data)
update
method updates an object of ResultType
using
the given new data of type DataType
, using some form of
"learning" algorithm.target
- The object to update.data
- The new data for the learning algorithm to use to update
the object.void update(ResultType target, java.lang.Iterable<? extends DataType> data)
update
method updates an object of ResultType
using
the given new Iterable containing some number of type DataType
,
using some form of "learning" algorithm.target
- The object to update.data
- The Iterable containing data for the learning algorithm to use to
update the object.