mosesdecoder/vw/README.md

Vowpal Wabbit for Moses

This is an attempt to integrate Vowpal Wabbit with Moses as a stateless feature function.

Implemented classifier features

• VWFeatureSourceBagOfWords: This creates a feature of form bow^token for every source sentence token.
• VWFeatureSourceExternalFeatures column=0: when used with -inputtype 5 (TabbedSentence) this can be used to supply additional feature to VW. The input is a tab-separated file, the first column is the usual input sentence, all other columns can be used for meta-data. Parameter column=0 counts beginning with the first column that is not the input sentence.
• VWFeatureSourceIndicator: Ass a feature for the whole source phrase.
• VWFeatureSourcePhraseInternal: Adds a separate feature for every word of the source phrase.
• VWFeatureSourceWindow size=3: Adds source words in a window of size 3 before and after the source phrase as features. These does not overlap with VWFeatureSourcePhraseInternal.
• VWFeatureTargetIndicator: Adds a feature for the whole target phrase.
• VWFeatureTargetPhraseInternal: Adds a separate feature for every word of the target phrase.

Configuration

To use the classifier edit your moses.ini

[features]
...
VW path=/home/username/vw/classifier1.vw
VWFeatureSourceBagOfWords
VWFeatureTargetIndicator
VWFeatureSourceIndicator
...
 
[weights]
...
VW0= 0.2
...

If you change the name of the main VW feature, remember to tell the VW classifier features which classifier they belong to:

[features]
...
VW name=bart path=/home/username/vw/classifier1.vw 
VWFeatureSourceBagOfWords used-by=bart
VWFeatureTargetIndicator used-by=bart
VWFeatureSourceIndicator used-by=bart
...

[weights]
...
bart= 0.2
...

You can also use multiple classifiers:

[features]
...
VW name=bart path=/home/username/vw/classifier1.vw 
VW path=/home/username/vw/classifier2.vw
VW path=/home/username/vw/classifier3.vw
VWFeatureSourceBagOfWords used-by=bart,VW0 
VWFeatureTargetIndicator used-by=VW1,VW0,bart
VWFeatureSourceIndicator used-by=bart,VW1
...

[weights]
...
bart= 0.2
VW0= 0.2
VW1= 0.2
...

Training the classifier

TODO