Package org.tribuo.common.nearest
Class KNNTrainer<T extends Output<T>>
java.lang.Object
org.tribuo.common.nearest.KNNTrainer<T>
- All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.config.Configurable
,com.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>
,Trainer<T>
A
Trainer
for k-nearest neighbour models.-
Nested Class Summary
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Field Summary
Fields inherited from interface org.tribuo.Trainer
DEFAULT_SEED, INCREMENT_INVOCATION_COUNT
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Constructor Summary
ConstructorDescriptionKNNTrainer
(int k, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend, NeighboursQueryFactory neighboursQueryFactory) Creates a K-NN trainer using the supplied parameters.KNNTrainer
(int k, KNNTrainer.Distance distance, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend) Deprecated.This Constructor is deprecated in version 4.3.KNNTrainer
(int k, Distance dist, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend, NeighboursQueryFactoryType nqFactoryType) Creates a K-NN trainer using the supplied parameters. -
Method Summary
Modifier and TypeMethodDescriptionint
The number of times this trainer instance has had it's train method invoked.void
Used by the OLCUT configuration system, and should not be called by external code.void
setInvocationCount
(int invocationCount) Set the internal state of the trainer to the provided number of invocations of the train method.toString()
train
(Dataset<T> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance) Trains a predictive model using the examples in the given data set.train
(Dataset<T> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance, int invocationCount) Trains a predictive model using the examples in the given data set.
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Constructor Details
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KNNTrainer
public KNNTrainer(int k, Distance dist, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend, NeighboursQueryFactoryType nqFactoryType) Creates a K-NN trainer using the supplied parameters.- Parameters:
k
- The number of nearest neighbours to consider.dist
- The distance function.numThreads
- The number of threads to use.combiner
- The combination function to aggregate the k predictions.backend
- The computational backend.nqFactoryType
- The nearest neighbour implementation factory to use.
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KNNTrainer
@Deprecated public KNNTrainer(int k, KNNTrainer.Distance distance, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend) Deprecated.This Constructor is deprecated in version 4.3.Creates a K-NN trainer using the supplied parameters.neighboursQueryFactory
defaults toNeighboursBruteForceFactory
.- Parameters:
k
- The number of nearest neighbours to consider.distance
- The distance function.numThreads
- The number of threads to use.combiner
- The combination function to aggregate the k predictions.backend
- The computational backend.
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KNNTrainer
public KNNTrainer(int k, int numThreads, EnsembleCombiner<T> combiner, KNNModel.Backend backend, NeighboursQueryFactory neighboursQueryFactory) Creates a K-NN trainer using the supplied parameters.- Parameters:
k
- The number of nearest neighbours to consider.numThreads
- The number of threads to use.combiner
- The combination function to aggregate the k predictions.backend
- The computational backend.neighboursQueryFactory
- The nearest neighbour implementation factory to use.
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Method Details
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postConfig
public void postConfig()Used by the OLCUT configuration system, and should not be called by external code.- Specified by:
postConfig
in interfacecom.oracle.labs.mlrg.olcut.config.Configurable
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train
public Model<T> train(Dataset<T> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance) Description copied from interface:Trainer
Trains a predictive model using the examples in the given data set. -
train
public Model<T> train(Dataset<T> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance, int invocationCount) Description copied from interface:Trainer
Trains a predictive model using the examples in the given data set.- Specified by:
train
in interfaceTrainer<T extends Output<T>>
- Parameters:
examples
- the data set containing the examples.runProvenance
- Training run specific provenance (e.g., fold number).invocationCount
- The invocation counter that the trainer should be set to before training, which in most cases alters the state of the RNG inside this trainer. If the value is set toTrainer.INCREMENT_INVOCATION_COUNT
then the invocation count is not changed.- Returns:
- a predictive model that can be used to generate predictions for new examples.
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toString
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getInvocationCount
public int getInvocationCount()Description copied from interface:Trainer
The number of times this trainer instance has had it's train method invoked.This is used to determine how many times the trainer's RNG has been accessed to ensure replicability in the random number stream.
- Specified by:
getInvocationCount
in interfaceTrainer<T extends Output<T>>
- Returns:
- The number of train invocations.
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setInvocationCount
public void setInvocationCount(int invocationCount) Description copied from interface:Trainer
Set the internal state of the trainer to the provided number of invocations of the train method.This is used when reproducing a Tribuo-trained model by setting the state of the RNG to what it was at when Tribuo trained the original model by simulating invocations of the train method. This method should ALWAYS be overridden, and the default method is purely for compatibility.
In a future major release this default implementation will be removed.
- Specified by:
setInvocationCount
in interfaceTrainer<T extends Output<T>>
- Parameters:
invocationCount
- the number of invocations of the train method to simulate
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getProvenance
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DistanceType