label

Providing user feedback on the training pairs

This phase opens an interactive learner where the user can mark the pairs found by findTrainingData phase as matches or non matches. The findTrainingData phase generates edge cases for labelling and the label phase helps the user to mark them.

./zingg.sh --phase label --conf config.json

Shows records and asks user to mark yes, no, cant say on the cli.

Proceed running findTrainingData followed by label phases till you have at least 30-40 positives, or when you see the predictions by Zingg converging with the output you want. At each stage, the user will get different variations of attributes across the records. Zingg performs pretty well with even small number of training, as the samples to be labelled are chosen by the algorithm itself.