Zingg-0.3.4
  • Welcome to Zingg
  • Step-By-Step Guide
    • Installation
      • Docker
        • Sharing custom data and config files
        • Shared locations
        • File read/write permissions
        • Copying Files To and From the Container
      • Installing From Release
        • Single Machine Setup
        • Spark Cluster Checklist
        • Installing Zingg
        • Verifying The Installation
      • Compiling From Source
    • Hardware Sizing
    • Zingg Runtime Properties
    • Zingg Command Line
    • Configuration
      • Configuring Through Environment Variables
      • Data Input and Output
        • Input Data
        • Output
      • Field Definitions
      • Model Location
      • Tuning Label, Match And Link Jobs
      • Telemetry
    • Working With Training Data
      • Finding Records For Training Set Creation
      • Labeling Records
      • Find And Label
      • Using pre-existing training data
      • Updating Labeled Pairs
      • Exporting Labeled Data
    • Building and saving the model
    • Finding the matches
    • Linking across datasets
  • Data Sources and Sinks
    • Zingg Pipes
    • Snowflake
    • JDBC
      • Postgres
      • MySQL
    • Cassandra
    • MongoDB
    • Neo4j
    • Parquet
    • BigQuery
  • Working With Python
  • Running Zingg on Cloud
    • Running on AWS
    • Running on Azure
    • Running on Databricks
  • Zingg Models
    • Pre-trained models
  • Improving Accuracy
    • Ignoring Commonly Occuring Words While Matching
    • Defining Domain Specific Blocking And Similarity Functions
  • Documenting The Model
  • Interpreting Output Scores
  • Reporting bugs and contributing
    • Setting Zingg Development Environment
  • Community
  • Frequently Asked Questions
  • Reading Material
  • Security And Privacy
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  1. Step-By-Step Guide
  2. Working With Training Data

Using pre-existing training data

Instructions on using existing training data with Zingg

PreviousFind And LabelNextUpdating Labeled Pairs

Last updated 2 years ago

Supplementing Zingg with existing training data

If you already have some training data that you want to start with, you can use that as well with Zingg. Add an attribute trainingSamples to the config and define the training pairs.

The training data supplied to Zingg should have a z_cluster column that groups the records together. It also needs the z_isMatch column which is 1 if the pairs match or 0 if they do not match.

An example is provided in .

The above training data can be specified using

In addition, labeled data of one model can also be exported and used as training data for another model. For details, check out .

Please note: It is advisable to still run and a few rounds to tune Zingg with the supplied training data as well as patterns it needs to learn independently.

Github training data
trainingSamples attribute in the configuration.
exporting labeled data
findTrainingData
label