Zingg-0.3.3
  • Welcome to Zingg
  • Step By Step Guide
    • Installation
      • Working with Docker Image
    • Hardware Sizing
    • Configuration
    • Creating training data
      • findTrainingData
      • label
      • findAndLabel
      • Using preexisting training data
      • Exporting labeled data as csv
    • Building and saving the model
    • Finding the matches
    • Linking across datasets
  • Data Sources and Sinks
    • Zingg Pipes
    • Snowflake
    • Cassandra
    • MongoDB
    • Neo4j
    • Parquet
  • Running Zingg on Cloud
    • Running on AWS
    • Running on Azure
    • Running on Databricks
  • Zingg Models
    • Pretrained models
  • Improving Accuracy By Defining Own Functions
  • Generating Documentation
  • Output Scores
  • Security And Privacy
  • Updating Labeled Pairs
  • Reporting bugs and contributing
  • Community
  • Frequently Asked Questions
  • Reading Material
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  1. Step By Step Guide
  2. Creating training data

findAndLabel

This phase is composed of two phases namely findTrainingData and label. This will help experienced users to quicken the process of creating Training data.

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

It's note that this option is good for small datasets else if your findTrainingData takes a long time, the user will have to wait for the console for labelling. For details, refer to the individual phases: findTrainingData and label

PreviouslabelNextUsing preexisting training data

Last updated 2 years ago