Class KernelSVMTrainer
java.lang.Object
org.tribuo.classification.sgd.kernel.KernelSVMTrainer
- All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.config.Configurable
,com.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>
,Trainer<Label>
,WeightedExamples
A trainer for a kernelised model using the Pegasos optimiser.
The Pegasos optimiser is extremely sensitive to the lambda parameter, and this value must be tuned to get good performance.
See:
Shalev-Shwartz S, Singer Y, Srebro N, Cotter A "Pegasos: Primal Estimated Sub-Gradient Solver for SVM" Mathematical Programming, 2011.
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Field Summary
Fields inherited from interface org.tribuo.Trainer
DEFAULT_SEED
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Constructor Summary
ConstructorsConstructorDescriptionKernelSVMTrainer
(Kernel kernel, double lambda, int epochs, int loggingInterval, long seed) Constructs a trainer for a kernel SVM model.KernelSVMTrainer
(Kernel kernel, double lambda, int epochs, long seed) Constructs a trainer for a kernel SVM model. -
Method Summary
Modifier and TypeMethodDescriptionint
The number of times this trainer instance has had it's train method invoked.void
void
setShuffle
(boolean shuffle) Turn on or off shuffling of examples.toString()
train
(Dataset<Label> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance) Trains a predictive model using the examples in the given data set.
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Constructor Details
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KernelSVMTrainer
Constructs a trainer for a kernel SVM model.- Parameters:
kernel
- The kernel function to use as a similarity measure.lambda
- l2 regulariser on the support vectors.epochs
- The number of epochs (complete passes through the training data).loggingInterval
- Log the loss after this many iterations. If -1 don't log anything.seed
- A seed for the random number generator, used to shuffle the examples before each epoch.
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KernelSVMTrainer
Constructs a trainer for a kernel SVM model. Sets the logging interval to 1000.- Parameters:
kernel
- The kernel function to use as a similarity measure.lambda
- l2 regulariser on the support vectors.epochs
- The number of epochs (complete passes through the training data).seed
- A seed for the random number generator, used to shuffle the examples before each epoch.
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Method Details
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postConfig
- Specified by:
postConfig
in interfacecom.oracle.labs.mlrg.olcut.config.Configurable
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setShuffle
Turn on or off shuffling of examples.This isn't exposed in the constructor as it defaults to on. This method should only be used for debugging.
- Parameters:
shuffle
- If true shuffle the examples, if false leave them in their current order.
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train
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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<Label>
- Returns:
- The number of train invocations.
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toString
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getProvenance
- Specified by:
getProvenance
in interfacecom.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>
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