Class KMeansModel
- All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>
,Serializable
The predict method of this model assigns centres to the provided input, but it does not update the model's centroids.
The predict method is single threaded.
See:
J. Friedman, T. Hastie, & R. Tibshirani. "The Elements of Statistical Learning" Springer 2001. PDF
- See Also:
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Field Summary
Fields inherited from class org.tribuo.Model
ALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput
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Method Summary
Modifier and TypeMethodDescriptionprotected KMeansModel
copy
(String newName, ModelProvenance newProvenance) Copies a model, replacing it's provenance and name with the supplied values.Returns a copy of the centroids.Generates an excuse for an example.getTopFeatures
(int n) Gets the topn
features associated with this model.Uses the model to predict the output for a single example.Methods inherited from class org.tribuo.Model
copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, predict, setName, toString, validate
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Method Details
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getCentroidVectors
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predict
Description copied from class:Model
Uses the model to predict the output for a single example.predict does not mutate the example.
Throws
IllegalArgumentException
if the example has no features or no feature overlap with the model. -
getTopFeatures
Description copied from class:Model
Gets the topn
features associated with this model.If the model does not produce per output feature lists, it returns a map with a single element with key Model.ALL_OUTPUTS.
If the model cannot describe it's top features then it returns
Collections.emptyMap()
.- Specified by:
getTopFeatures
in classModel<ClusterID>
- Parameters:
n
- the number of features to return. If this value is less than 0, all features should be returned for each class, unless the model cannot score it's features.- Returns:
- a map from string outputs to an ordered list of pairs of feature names and weights associated with that feature in the model
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getExcuse
Description copied from class:Model
Generates an excuse for an example.This attempts to explain a classification result. Generating an excuse may be quite an expensive operation.
This excuse either contains per class information or an entry with key Model.ALL_OUTPUTS.
The optional is empty if the model does not provide excuses.
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copy
Description copied from class:Model
Copies a model, replacing it's provenance and name with the supplied values.Used to provide the provenance removal functionality.
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