CategoryType
- The type of output categories. Can be any type that has a valid
equals and hashCode method.@PublicationReference(title="Ultraconservative online algorithms for multiclass problems", author={"Koby Crammer","Yoram Singer"}, year=2003, type=Journal, publication="The Journal of Machine Learning Research", pages={951,991}, url="http://portal.acm.org/citation.cfm?id=944936") public static class OnlineMultiPerceptron.UniformUpdate<CategoryType> extends OnlineMultiPerceptron<CategoryType>
OnlineMultiPerceptron.ProportionalUpdate<CategoryType>, OnlineMultiPerceptron.UniformUpdate<CategoryType>
DEFAULT_MIN_MARGIN, minMargin, vectorFactory
Constructor and Description |
---|
UniformUpdate()
Creates a new
OnlineMultiPerceptron.UniformUpdate . |
UniformUpdate(double minMargin)
Creates a new
OnlineMultiPerceptron.UniformUpdate with the
given minimum margin. |
UniformUpdate(double minMargin,
VectorFactory<?> vectorFactory)
Creates a new
OnlineMultiPerceptron.UniformUpdate with the
given minimum margin and backing vector factory. |
Modifier and Type | Method and Description |
---|---|
void |
update(LinearMultiCategorizer<CategoryType> target,
InputOutputPair<? extends Vectorizable,CategoryType> example)
The
update method updates an object of ResultType using
the given new data of type DataType , using some form of
"learning" algorithm. |
createInitialLearnedObject, getMinMargin, getVectorFactory, setMinMargin, setVectorFactory
clone, learn, learn, update
public UniformUpdate()
OnlineMultiPerceptron.UniformUpdate
.public UniformUpdate(double minMargin)
OnlineMultiPerceptron.UniformUpdate
with the
given minimum margin.minMargin
- The minimum margin to consider an example correct.public UniformUpdate(double minMargin, VectorFactory<?> vectorFactory)
OnlineMultiPerceptron.UniformUpdate
with the
given minimum margin and backing vector factory.minMargin
- The minimum margin to consider an example correct.vectorFactory
- The vector factory used to create the weight vectors.public void update(LinearMultiCategorizer<CategoryType> target, InputOutputPair<? extends Vectorizable,CategoryType> example)
IncrementalLearner
update
method updates an object of ResultType
using
the given new data of type DataType
, using some form of
"learning" algorithm.update
in interface IncrementalLearner<InputOutputPair<? extends Vectorizable,CategoryType>,LinearMultiCategorizer<CategoryType>>
update
in class OnlineMultiPerceptron<CategoryType>
target
- The object to update.example
- The new data for the learning algorithm to use to update
the object.