public class SvmHmmAdapter extends Object implements TcShallowLearningAdapter
http://www.cs.cornell.edu/people/tj/svm_light/svm_hmm.html
for parameter settings.
Parameters: -c Typical SVM parameter C trading-off slack vs. magnitude of the weight-vector. NOTE: The default value for this parameter is unlikely to work well for your particular problem. A good value for C must be selected via cross-validation, ideally exploring values over several orders of magnitude. NOTE: Unlike in V1.01, the value of C is divided by the number of training examples. So, to get results equivalent to V1.01, multiply C by the number of training examples. Default value is set to 1. -e Parameter "-e <EPSILON>": This specifies the precision to which constraints are required to be satisfied by the solution. The smaller EPSILON, the longer and the more memory training takes, but the solution is more precise. However, solutions more accurate than 0.5 typically do not improve prediction accuracy. -t Order of dependencies of transitions in HMM. Can be any number larger than 1. (default 1) -m Order of dependencies of emissions in HMM. Can be any number larger than 0. (default 0) UPDATE: according to svm_struct_api.c: must be either 0 or 1; fails for >1 -b A non-zero value turns on (approximate) beam search to replace the exact Viterbi algorithm both for finding the most violated constraint, as well as for computing predictions. The value is the width of the beam used (e.g. 100). (default 0).
Constructor and Description |
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SvmHmmAdapter() |
Modifier and Type | Method and Description |
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String |
getDataWriterClass() |
org.dkpro.lab.task.impl.DimensionBundle<Collection<String>> |
getFoldDimensionBundle(String[] files,
int folds) |
Class<? extends ModelSerialization_ImplBase> |
getLoadModelConnectorClass() |
Class<? extends org.dkpro.lab.reporting.ReportBase> |
getMajorityClassBaselineIdReportClass() |
String |
getName() |
Class<? extends org.dkpro.lab.reporting.ReportBase> |
getOutcomeIdReportClass() |
Class<? extends org.dkpro.lab.reporting.ReportBase> |
getRandomBaselineIdReportClass() |
ModelSerializationTask |
getSaveModelTask() |
org.dkpro.lab.task.impl.ExecutableTaskBase |
getTestTask() |
String |
toString() |
boolean |
useSparseFeatures() |
public org.dkpro.lab.task.impl.ExecutableTaskBase getTestTask()
getTestTask
in interface TcShallowLearningAdapter
public Class<? extends org.dkpro.lab.reporting.ReportBase> getOutcomeIdReportClass()
getOutcomeIdReportClass
in interface TcShallowLearningAdapter
public Class<? extends org.dkpro.lab.reporting.ReportBase> getMajorityClassBaselineIdReportClass()
getMajorityClassBaselineIdReportClass
in interface TcShallowLearningAdapter
public Class<? extends org.dkpro.lab.reporting.ReportBase> getRandomBaselineIdReportClass()
getRandomBaselineIdReportClass
in interface TcShallowLearningAdapter
public org.dkpro.lab.task.impl.DimensionBundle<Collection<String>> getFoldDimensionBundle(String[] files, int folds)
getFoldDimensionBundle
in interface TcShallowLearningAdapter
public String getDataWriterClass()
getDataWriterClass
in interface TcShallowLearningAdapter
public Class<? extends ModelSerialization_ImplBase> getLoadModelConnectorClass()
getLoadModelConnectorClass
in interface TcShallowLearningAdapter
public ModelSerializationTask getSaveModelTask()
getSaveModelTask
in interface TcShallowLearningAdapter
public boolean useSparseFeatures()
useSparseFeatures
in interface TcShallowLearningAdapter
public String getName()
getName
in interface TcShallowLearningAdapter
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