synthcity
A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation. (by vanderschaarlab)
MTR
The official implementation of the paper "Rethinking Data Augmentation for Tabular Data in Deep Learning" (by somaonishi)
synthcity | MTR | |
---|---|---|
4 | 1 | |
362 | 9 | |
4.4% | - | |
7.2 | 4.9 | |
15 days ago | 7 months ago | |
Python | Python | |
Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
synthcity
Posts with mentions or reviews of synthcity.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-19.
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Benchmark synthetic tabular data generators using Syunthcity
Library: https://github.com/vanderschaarlab/synthcity
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Tired of synthetic corgi?Check out Synthcity,a tool for synthetic tabular data
Synthcity is a library for generating and benchmarking synthetic tabular data. https://github.com/vanderschaarlab/synthcity
Synthcity includes a wide range of algorithms for various use cases, such as:
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[P] Tired of generating synthetic corgis❓🐶 Check out Synthcity, a framework for synthetic tabular data
🌟 Synthcity isa library for generating and benchmarking synthetic tabular data. https://github.com/vanderschaarlab/synthcity
MTR
Posts with mentions or reviews of MTR.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Rethinking Data Augmentation for Tabular Data in Deep Learning
Tabular data is the most widely used data format in machine learning (ML). While tree-based methods outperform DL-based methods in supervised learning, recent literature reports that self-supervised learning with Transformer-based models outperforms tree-based methods. In the existing literature on self-supervised learning for tabular data, contrastive learning is the predominant method. In contrastive learning, data augmentation is important to generate different views. However, data augmentation for tabular data has been difficult due to the unique structure and high complexity of tabular data. In addition, three main components are proposed together in existing methods: model structure, self-supervised learning methods, and data augmentation. Therefore, previous works have compared the performance without comprehensively considering these components, and it is not clear how each component affects the actual performance. In this study, we focus on data augmentation to address these issues. We propose a novel data augmentation method, $\textbf{M}$ask $\textbf{T}$oken $\textbf{R}$eplacement ($\texttt{MTR}$), which replaces the mask token with a portion of each tokenized column; $\texttt{MTR}$ takes advantage of the properties of Transformer, which is becoming the predominant DL-based architecture for tabular data, to perform data augmentation for each column embedding. Through experiments with 13 diverse public datasets in both supervised and self-supervised learning scenarios, we show that $\texttt{MTR}$ achieves competitive performance against existing data augmentation methods and improves model performance. In addition, we discuss specific scenarios in which $\texttt{MTR}$ is most effective and identify the scope of its application. The code is available at https://github.com/somaonishi/MTR/.
What are some alternatives?
When comparing synthcity and MTR you can also consider the following projects:
Papers-in-100-Lines-of-Code - Implementation of papers in 100 lines of code.
rtdl - Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl]
rtdl - Research on Tabular Deep Learning [Moved to: https://github.com/yandex-research/rtdl]
tabular-dl-pretrain-objectives - Revisiting Pretrarining Objectives for Tabular Deep Learning