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Original file line number | Diff line number | Diff line change |
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--- | ||
layout: default | ||
title: Find the matches | ||
parent: Step By Step Guide | ||
nav_order: 8 | ||
description: Identifying matching records | ||
--- | ||
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# Finding the matches | ||
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Finds the records which match with each other. | ||
### match | ||
Finds the records which match with each other. | ||
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`./zingg.sh --phase match --conf config.json` | ||
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As can be seen in the image below, matching records are given the same z\_cluster id. Each record also gets a z\_minScore and z\_maxScore which shows the least/greatest it matched with other records in the same cluster. | ||
As can be seen in the image below, matching records are given the same z_cluster id. Each record also gets a z_minScore and z_maxScore which shows the least/greatest it matched with other records in the same cluster. | ||
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![Match results](../../assets/match.gif) | ||
![Match results](/assets/match.gif) | ||
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If records across multiple sources have to be matched, the [link phase](link.md) should be used. | ||
If records across multiple sources have to be matched, the [link phase](./link.md) should be used. |
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--- | ||
layout: default | ||
title: Build and save the model | ||
parent: Step By Step Guide | ||
nav_order: 7 | ||
description: Guide to build and save model | ||
--- | ||
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# Building and saving the model | ||
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### train - training and saving the models | ||
Builds up the Zingg models using the training data from the above phases and writes them to the folder zinggDir/modelId as specified in the config. | ||
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``` | ||
./zingg.sh --phase train --conf config.json | ||
``` | ||
./zingg.sh --phase train --conf config.json |
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docs/stepbystep/configuration/tuning-label-match-and-link-jobs.md
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--- | ||
description: A whole new way to work with Zingg! | ||
--- | ||
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# Working With Python | ||
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Instead of configuring Zingg using the JSON, we can now use Python to build and run Zingg entity and identity resolution programs. This is handy when you want to run Zingg on an existing Spark cluster. To run on local machine, please do the installation of the release before running Zingg python programs. | ||
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The Zingg Python package can be installed by invoking | ||
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`python -m pip install zingg` | ||
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Detailed documentation of the python api is available at [https://readthedocs.org/projects/zingg/](https://readthedocs.org/projects/zingg/) | ||
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Example programs for python exist under examples/febrl | ||
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`` | ||
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