cc.mallet.classify
Class WinnowTrainer
java.lang.Object
   cc.mallet.classify.ClassifierTrainer<Winnow>
cc.mallet.classify.ClassifierTrainer<Winnow>
       cc.mallet.classify.WinnowTrainer
cc.mallet.classify.WinnowTrainer
- public class WinnowTrainer 
- extends ClassifierTrainer<Winnow>
An implementation of the training methods of a 
 Winnow2 on-line classifier. Given an instance xi,
 the algorithm computes Sum(xi*wi), where wi is 
 the weight for that feature in the given class. 
 If the Sum is greater than some threshold 
 theta, then the classifier guess
 true for that class. 
 Only when the classifier makes a mistake are the 
 weights updated in one of two steps:
 Promote: guessed 0 and answer was 1. Multiply
 all weights of present features by alpha.
 Demote: guessed 1 and answer was 0. Divide
 all weights of present features by beta.
 Limitations: Winnow2 only considers binary feature
 vectors (i.e. whether or not the feature is present,
 not its value).
 
 
 
 
| Constructor Summary | 
| WinnowTrainer()Default constructor.
 | 
| WinnowTrainer(double a,
              double b)Sets alpha and beta and default value for theta
 | 
| WinnowTrainer(double a,
              double b,
              double nfact)Sets alpha, beta, and nfactor
 | 
 
 
 
| Methods inherited from class java.lang.Object | 
| clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait | 
 
WinnowTrainer
public WinnowTrainer()
- Default constructor. Sets all features to defaults.
 
WinnowTrainer
public WinnowTrainer(double a,
                     double b)
- Sets alpha and beta and default value for theta
 
- Parameters:
- a- alpha value
- b- beta value
 
WinnowTrainer
public WinnowTrainer(double a,
                     double b,
                     double nfact)
- Sets alpha, beta, and nfactor
 
- Parameters:
- a- alpha value
- b- beta value
- nfact- nfactor value
 
getClassifier
public Winnow getClassifier()
- 
- Specified by:
- getClassifierin class- ClassifierTrainer<Winnow>
 
- 
 
train
public Winnow train(InstanceList trainingList)
- Trains winnow on the instance list, updating 
 weightsaccording to errors
 
- 
- Specified by:
- trainin class- ClassifierTrainer<Winnow>
 
- 
- Parameters:
- ilist- Instance list to be trained on
- Returns:
- Classifier object containing learned weights