public final class XGBoostExternalModel<T extends Output<T>> extends ExternalModel<T,ml.dmlc.xgboost4j.java.DMatrix,float[][]>
Model which wraps around a XGBoost.Booster which was trained by a system other than Tribuo.
XGBoost is a fast implementation of gradient boosted decision trees.
Throws IllegalStateException if the XGBoost C++ library fails to load or throws an exception.
See:
Chen T, Guestrin C. "XGBoost: A Scalable Tree Boosting System" Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016.
and for the original algorithm:
Friedman JH. "Greedy Function Approximation: a Gradient Boosting Machine" Annals of statistics, 2001.
N.B.: XGBoost4J wraps the native C implementation of xgboost that links to various C libraries, including libgomp and glibc (on Linux). If you're running on Alpine, which does not natively use glibc, you'll need to install glibc into the container. On the macOS binary on Maven Central is compiled without OpenMP support, meaning that XGBoost is single threaded on macOS. You can recompile the macOS binary with OpenMP support after installing libomp from homebrew if necessary.
| Modifier and Type | Field and Description |
|---|---|
protected ml.dmlc.xgboost4j.java.Booster |
model
Transient as we rely upon the native serialisation mechanism to bytes rather than Java serializing the Booster.
|
DEFAULT_BATCH_SIZE, featureBackwardMapping, featureForwardMappingALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput| Modifier and Type | Method and Description |
|---|---|
protected ml.dmlc.xgboost4j.java.DMatrix |
convertFeatures(SparseVector input)
Converts from a SparseVector using the external model's indices into
the ingestion format for the external model.
|
protected ml.dmlc.xgboost4j.java.DMatrix |
convertFeaturesList(List<SparseVector> input)
Converts from a list of SparseVector using the external model's indices
into the ingestion format for the external model.
|
protected List<Prediction<T>> |
convertOutput(float[][] output,
int[] numValidFeatures,
List<Example<T>> examples)
Converts the output of the external model into a list of
Predictions. |
protected Prediction<T> |
convertOutput(float[][] output,
int numValidFeatures,
Example<T> example)
Converts the output of the external model into a
Prediction. |
protected XGBoostExternalModel<T> |
copy(String newName,
ModelProvenance newProvenance)
Copies a model, replacing it's provenance and name with the supplied values.
|
static <T extends Output<T>> |
createXGBoostModel(OutputFactory<T> factory,
Map<String,Integer> featureMapping,
Map<T,Integer> outputMapping,
XGBoostOutputConverter<T> outputFunc,
ml.dmlc.xgboost4j.java.Booster model,
Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> instanceProvenance)
Creates an
XGBoostExternalModel from the supplied in-memory XGBoost Booster. |
static <T extends Output<T>> |
createXGBoostModel(OutputFactory<T> factory,
Map<String,Integer> featureMapping,
Map<T,Integer> outputMapping,
XGBoostOutputConverter<T> outputFunc,
ml.dmlc.xgboost4j.java.Booster model,
URL provenanceLocation)
Deprecated.
As the URL argument must always be valid. To wrap an in-memory booster use
createXGBoostModel(OutputFactory, Map, Map, XGBoostOutputConverter, Booster, Map). |
static <T extends Output<T>> |
createXGBoostModel(OutputFactory<T> factory,
Map<String,Integer> featureMapping,
Map<T,Integer> outputMapping,
XGBoostOutputConverter<T> outputFunc,
Path path)
Creates an
XGBoostExternalModel from the supplied model on disk. |
static <T extends Output<T>> |
createXGBoostModel(OutputFactory<T> factory,
Map<String,Integer> featureMapping,
Map<T,Integer> outputMapping,
XGBoostOutputConverter<T> outputFunc,
String path)
Creates an
XGBoostExternalModel from the supplied model on disk. |
protected float[][] |
externalPrediction(ml.dmlc.xgboost4j.java.DMatrix input)
Runs the external model's prediction function.
|
List<XGBoostFeatureImportance> |
getFeatureImportance()
Creates objects to report feature importance metrics for XGBoost.
|
Map<String,List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> |
getTopFeatures(int n)
Gets the top
n features associated with this model. |
createFeatureMap, createOutputInfo, getBatchSize, getExcuse, innerPredict, predict, setBatchSizecopy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, predict, predict, setName, toString, validateprotected transient ml.dmlc.xgboost4j.java.Booster model
protected ml.dmlc.xgboost4j.java.DMatrix convertFeatures(SparseVector input)
ExternalModelconvertFeatures in class ExternalModel<T extends Output<T>,ml.dmlc.xgboost4j.java.DMatrix,float[][]>input - The features using external indices.protected ml.dmlc.xgboost4j.java.DMatrix convertFeaturesList(List<SparseVector> input)
ExternalModelconvertFeaturesList in class ExternalModel<T extends Output<T>,ml.dmlc.xgboost4j.java.DMatrix,float[][]>input - The features using external indices.protected float[][] externalPrediction(ml.dmlc.xgboost4j.java.DMatrix input)
ExternalModelexternalPrediction in class ExternalModel<T extends Output<T>,ml.dmlc.xgboost4j.java.DMatrix,float[][]>input - The input in the external model's format.protected Prediction<T> convertOutput(float[][] output, int numValidFeatures, Example<T> example)
ExternalModelPrediction.convertOutput in class ExternalModel<T extends Output<T>,ml.dmlc.xgboost4j.java.DMatrix,float[][]>output - The output of the external model.numValidFeatures - The number of valid features in the input.example - The input example, used to construct the Prediction.protected List<Prediction<T>> convertOutput(float[][] output, int[] numValidFeatures, List<Example<T>> examples)
ExternalModelPredictions.convertOutput in class ExternalModel<T extends Output<T>,ml.dmlc.xgboost4j.java.DMatrix,float[][]>output - The output of the external model.numValidFeatures - An array with the number of valid features in each example.examples - The input examples, used to construct the Predictions.public List<XGBoostFeatureImportance> getFeatureImportance()
XGBoostFeatureImportance
for more information on what those metrics mean. Typically this list will contain a single instance for the entire
model. For multidimensional regression the list will have one entry per dimension, in dimension order.public Map<String,List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> getTopFeatures(int n)
Modeln 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<T extends Output<T>>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.protected XGBoostExternalModel<T> copy(String newName, ModelProvenance newProvenance)
ModelUsed to provide the provenance removal functionality.
public static <T extends Output<T>> XGBoostExternalModel<T> createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, String path)
XGBoostExternalModel from the supplied model on disk.T - The type of the output.factory - The output factory to use.featureMapping - The feature mapping between Tribuo names and XGBoost integer ids.outputMapping - The output mapping between Tribuo outputs and XGBoost integer ids.outputFunc - The XGBoostOutputConverter function for the output type.path - The path to the model on disk.public static <T extends Output<T>> XGBoostExternalModel<T> createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, Path path)
XGBoostExternalModel from the supplied model on disk.T - The type of the output.factory - The output factory to use.featureMapping - The feature mapping between Tribuo names and XGBoost integer ids.outputMapping - The output mapping between Tribuo outputs and XGBoost integer ids.outputFunc - The XGBoostOutputConverter function for the output type.path - The path to the model on disk.@Deprecated public static <T extends Output<T>> XGBoostExternalModel<T> createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, ml.dmlc.xgboost4j.java.Booster model, URL provenanceLocation)
createXGBoostModel(OutputFactory, Map, Map, XGBoostOutputConverter, Booster, Map).XGBoostExternalModel from the supplied model.
Note: the provenance system requires that the URL point to a valid local file and will throw an exception if it is not. However it doesn't check that the file is where the Booster was created from.
T - The type of the output.factory - The output factory to use.featureMapping - The feature mapping between Tribuo names and XGBoost integer ids.outputMapping - The output mapping between Tribuo outputs and XGBoost integer ids.outputFunc - The XGBoostOutputConverter function for the output type.model - The XGBoost model to wrap.provenanceLocation - The location where the model was loaded from.public static <T extends Output<T>> XGBoostExternalModel<T> createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, ml.dmlc.xgboost4j.java.Booster model, Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> instanceProvenance)
XGBoostExternalModel from the supplied in-memory XGBoost Booster.T - The type of the output.factory - The output factory to use.featureMapping - The feature mapping between Tribuo names and XGBoost integer ids.outputMapping - The output mapping between Tribuo outputs and XGBoost integer ids.outputFunc - The XGBoostOutputConverter function for the output type.model - The XGBoost model to wrap.instanceProvenance - Provenance for this model.Copyright © 2015–2021 Oracle and/or its affiliates. All rights reserved.