@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, updatecreateInitialLearnedObject, getVectorFactory, setVectorFactory, updateupdateclone, learn, learn, updateequals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitupdatelearnlearncreateInitialLearnedObject, update, updateclonepublic 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)
AbstractOnlineLinearBinaryCategorizerLearnerupdate method updates an object of ResultType using
the given a new supervised input-output pair, using some form of
"learning" algorithm.update in class AbstractOnlineLinearBinaryCategorizerLearnertarget - 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)
KernelizableBinaryCategorizerOnlineLearnerInputType - 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).