dblink
reclin
dblink | reclin | |
---|---|---|
1 | 1 | |
54 | 56 | |
- | - | |
0.0 | 0.0 | |
almost 3 years ago | over 1 year ago | |
Scala | R | |
GNU General Public License v3.0 or later | - |
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dblink
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[D] Machine Learning and "Record Linkage"
Felligi-Sunter is the baseline model in record linkage research. It is implemented in R in fastLink and RecordLinkage, but you will need training data. There are some other options, e.g. dblink, that use Bayesian methods and a latent variable set up so you don’t need training data.
reclin
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[D] Machine Learning and "Record Linkage"
When researching this topic, I found algorithms like this (in R): https://github.com/djvanderlaan/reclin
What are some alternatives?
entity-embed - PyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.
splink - Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
sparkMeasure - This is the development repository for sparkMeasure, a tool and library designed for efficient analysis and troubleshooting of Apache Spark jobs. It focuses on easing the collection and examination of Spark metrics, making it a practical choice for both developers and data engineers.
delight - A Spark UI and Spark History Server alternative with CPU and Memory metrics! Delight is free, cross-platform, and open-source.