public class LibSVMRegressionModel extends LibSVMModel<Regressor>
See:
Chang CC, Lin CJ. "LIBSVM: a library for Support Vector Machines" ACM transactions on intelligent systems and technology (TIST), 2011.for the nu-svr algorithm:
Schölkopf B, Smola A, Williamson R, Bartlett P L. "New support vector algorithms" Neural Computation, 2000, 1207-1245.and for the original algorithm:
Cortes C, Vapnik V. "Support-Vector Networks" Machine Learning, 1995.
models
ALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput
Modifier and Type | Method and Description |
---|---|
protected LibSVMRegressionModel |
copy(String newName,
ModelProvenance newProvenance)
Copies a model, replacing it's provenance and name with the supplied values.
|
Map<String,Integer> |
getNumberOfSupportVectors()
Returns the support vectors used for each dimension.
|
Prediction<Regressor> |
predict(Example<Regressor> example)
Uses the model to predict the output for a single example.
|
copyModel, getExcuse, getInnerModels, getModel, getTopFeatures
copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, predict, setName, toString, validate
public Map<String,Integer> getNumberOfSupportVectors()
public Prediction<Regressor> predict(Example<Regressor> example)
Model
predict does not mutate the example.
Throws IllegalArgumentException
if the example has no features
or no feature overlap with the model.
protected LibSVMRegressionModel copy(String newName, ModelProvenance newProvenance)
Model
Used to provide the provenance removal functionality.
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