edu.umass.cs.mallet.base.classify
Class ClassifierTrainer
java.lang.Object
edu.umass.cs.mallet.base.classify.ClassifierTrainer
- Direct Known Subclasses:
- AdaBoostM2Trainer, AdaBoostTrainer, BaggingTrainer, BalancedWinnowTrainer, C45Trainer, ConfidencePredictingClassifierTrainer, DecisionTreeTrainer, FeatureSelectingClassifierTrainer, IncrementalClassifierTrainer, MaxEntTrainer, MCMaxEntTrainer, WinnowTrainer
- public abstract class ClassifierTrainer
- extends java.lang.Object
Abstract parent of all classifier trainers.
All classification techniques in MALLET are implement as two classes:
a trainer and a classifier. The trainer injests the training data
and creates a classifier that holds the parameters set during training.
The classifier applies those parameters to an Instance to produce
a classification of the Instance.
A concrete trainer is required only to be able to train from an InstanceList.
Trainers that can incrementally train are subclasses of IncrementalTrainingClassifier.
There are some rudimentary command line facilities here. The preferred
command line interface tools for document classification are:
Csv2Vectors
,
Text2Vectors
,
Vectors2Classify
,
Vectors2Info
, and
Vectors2Vectors
- See Also:
Classifier
Method Summary |
static void |
main(java.lang.String[] args)
|
java.lang.String |
toString()
|
Classifier |
train(InstanceList trainingSet)
|
Classifier |
train(InstanceList trainingSet,
InstanceList validationSet)
|
Classifier |
train(InstanceList trainingSet,
InstanceList validationSet,
InstanceList testSet)
|
Classifier |
train(InstanceList trainingSet,
InstanceList validationSet,
InstanceList testSet,
ClassifierEvaluating evaluator)
|
abstract Classifier |
train(InstanceList trainingSet,
InstanceList validationSet,
InstanceList testSet,
ClassifierEvaluating evaluator,
Classifier initialClassifier)
Return a new classifier tuned using the three arguments. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
ClassifierTrainer
public ClassifierTrainer()
train
public Classifier train(InstanceList trainingSet)
train
public Classifier train(InstanceList trainingSet,
InstanceList validationSet)
train
public Classifier train(InstanceList trainingSet,
InstanceList validationSet,
InstanceList testSet)
train
public Classifier train(InstanceList trainingSet,
InstanceList validationSet,
InstanceList testSet,
ClassifierEvaluating evaluator)
train
public abstract Classifier train(InstanceList trainingSet,
InstanceList validationSet,
InstanceList testSet,
ClassifierEvaluating evaluator,
Classifier initialClassifier)
- Return a new classifier tuned using the three arguments.
- Parameters:
trainingSet
- examples used to set parameters.validationSet
- examples used to tune meta-parameters. May be null.testSet
- examples not examined at all for training, but passed on to diagnostic routines. May be null.initialClassifier
- training process may start from here. The parameters of the initialClassifier are not modified. May be null.
toString
public java.lang.String toString()
main
public static void main(java.lang.String[] args)
throws bsh.EvalError,
java.io.IOException
- Throws:
bsh.EvalError
java.io.IOException