Class TransformedModel<T extends Output<T>>
- All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>
,Serializable
Model
with it's TransformerMap
so all Example
s are transformed
appropriately before the model makes predictions.
If the densify flag is set, densifies all incoming data before transforming it.
Transformations only operate on observed values. To operate on implicit zeros then
first call MutableDataset.densify()
on the datasets.
- 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 TransformedModel<T>
copy
(String name, ModelProvenance newProvenance) Copies a model, replacing its provenance and name with the supplied values.boolean
Returns true if the model densifies the feature space before applying the transformations.Generates an excuse for an example.Gets the inner model to allow access to any class specific methods that model contains (e.g., to examine cluster centroids).getTopFeatures
(int n) Gets the topn
features associated with this model.Gets the transformers that this model applies to each example.List<Prediction<T>>
Uses the model to predict the outputs for multiple examples contained in a data set.Uses the model to predict the output for a single example.Methods inherited from class org.tribuo.Model
castModel, copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, innerPredict, predict, setName, toString, validate
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Method Details
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getTransformerMap
Gets the transformers that this model applies to each example.Note if you use these transformers to modify some data, and then feed that data to this model, the data will be transformed twice and this is not what you want.
- Returns:
- The transformers.
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getInnerModel
Gets the inner model to allow access to any class specific methods that model contains (e.g., to examine cluster centroids).Note that this model expects all examples to have been transformed using the transformer map, which can be extracted with
getTransformerMap()
.- Returns:
- The inner model.
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getDensify
public boolean getDensify()Returns true if the model densifies the feature space before applying the transformations.- Returns:
- True if the transforms operate on the dense feature space.
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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. -
predict
Description copied from class:Model
Uses the model to predict the outputs for multiple examples contained in a data set.Throws
IllegalArgumentException
if the examples have 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<T extends Output<T>>
- 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 its provenance and name with the supplied values.Used to provide the provenance removal functionality.
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