public class KMeansModel extends Model<ClusterID>
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
ALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput
Modifier and Type | Method and Description |
---|---|
protected KMeansModel |
copy(String newName,
ModelProvenance newProvenance)
Copies a model, replacing it's provenance and name with the supplied values.
|
DenseVector[] |
getCentroidVectors()
Returns a copy of the centroids.
|
Optional<Excuse<ClusterID>> |
getExcuse(Example<ClusterID> example)
Generates an excuse for an example.
|
Map<String,List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> |
getTopFeatures(int n)
Gets the top
n features associated with this model. |
Prediction<ClusterID> |
predict(Example<ClusterID> example)
Uses the model to predict the output for a single example.
|
copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, predict, setName, toString, validate
public DenseVector[] getCentroidVectors()
public Prediction<ClusterID> predict(Example<ClusterID> example)
Model
predict does not mutate the example.
Throws IllegalArgumentException
if the example has no features
or no feature overlap with the model.
public Map<String,List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> getTopFeatures(int n)
Model
n
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()
.
getTopFeatures
in class Model<ClusterID>
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.public Optional<Excuse<ClusterID>> getExcuse(Example<ClusterID> example)
Model
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.
protected KMeansModel copy(String newName, ModelProvenance newProvenance)
Model
Used to provide the provenance removal functionality.
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