@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 class RelaxedOnlineMaximumMarginAlgorithm extends AbstractKernelizableBinaryCategorizerOnlineLearner
vectorFactory
Constructor and Description |
---|
RelaxedOnlineMaximumMarginAlgorithm()
Creates a new
RelaxedOnlineMaximumMarginAlgorithm . |
RelaxedOnlineMaximumMarginAlgorithm(VectorFactory<?> vectorFactory)
Creates a new
RelaxedOnlineMaximumMarginAlgorithm with
the given vector factory. |
Modifier and Type | Method and Description |
---|---|
<InputType> |
update(DefaultKernelBinaryCategorizer<InputType> target,
InputType input,
boolean label)
Performs a kernel-based incremental update step on the given object
using the given supervised data.
|
void |
update(LinearBinaryCategorizer target,
Vector input,
boolean label)
The
update method updates an object of ResultType using
the given a new supervised input-output pair, using some form of
"learning" algorithm. |
createInitialLearnedObject, createKernelLearner, learn, update, update, update
createInitialLearnedObject, getVectorFactory, setVectorFactory, update
update
clone, learn, learn, update
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
update
learn
learn
createInitialLearnedObject, update, update
clone
public RelaxedOnlineMaximumMarginAlgorithm()
RelaxedOnlineMaximumMarginAlgorithm
.public RelaxedOnlineMaximumMarginAlgorithm(VectorFactory<?> vectorFactory)
RelaxedOnlineMaximumMarginAlgorithm
with
the given vector factory.vectorFactory
- The vector factory to use.public void update(LinearBinaryCategorizer target, Vector input, boolean label)
AbstractOnlineLinearBinaryCategorizerLearner
update
method updates an object of ResultType
using
the given a new supervised input-output pair, using some form of
"learning" algorithm.update
in class AbstractOnlineLinearBinaryCategorizerLearner
target
- The object to update.input
- The supervised input vector to learn from.label
- The supervised output label to learn from.public <InputType> void update(DefaultKernelBinaryCategorizer<InputType> target, InputType input, boolean label)
KernelizableBinaryCategorizerOnlineLearner
InputType
- The input type for supervised learning. Will be passed to the
kernel function.target
- The target object to update.input
- The supervised input value.label
- The supervised output value (label).