Clearbox-AI / SURE
An open-source Python library for the assessment of utility and privacy performance of any tabular synthetic dataset.
☆23Updated last month
Alternatives and similar repositories for SURE:
Users that are interested in SURE are comparing it to the libraries listed below
- Clearbox AI's all-in-one solution for generation and evaluation of synthetic tabular and time-series data.☆42Updated this week
- A Python library to check for data quality and automatically generate data tests.☆42Updated last year
- A Python library to perform NER on structured data and generate PII with Faker☆29Updated 10 months ago
- An agnostic wrapper for the most common ML frameworks.☆14Updated 3 years ago
- Evaluate real and synthetic datasets against each other☆86Updated 3 months ago
- pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.☆36Updated this week
- Metrics to evaluate quality and efficacy of synthetic datasets.☆230Updated this week
- A library to generate synthetic tabular or RDF data using Conditional Generative Adversary Networks (GANs) combined with Differential Pri…☆38Updated last month
- Frouros: an open-source Python library for drift detection in machine learning systems.☆215Updated 2 months ago
- A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.☆225Updated last month
- Standardised Metrics and Methods for Synthetic Tabular Data Evaluation☆32Updated 8 months ago
- A Unified Framework for Quantifying Privacy Risk in Synthetic Data according to the GDPR☆84Updated last month
- Python Biella Group basic template for a modern generic python application☆12Updated this week
- A software package for privacy-preserving generation of a synthetic twin to a given sensitive data set.☆52Updated 7 months ago
- ☆35Updated last year
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆100Updated 2 years ago
- nbsynthetic is simple and robust tabular synthetic data generation library for small and medium size datasets☆65Updated 2 years ago
- Missing data amputation and exploration functions for Python☆68Updated 2 years ago
- Effector - a Python package for global and regional effect methods☆84Updated this week
- A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.☆533Updated 3 months ago
- A novel approach for synthesizing tabular data using pretrained large language models☆309Updated 5 months ago
- Editing machine learning models to reflect human knowledge and values☆124Updated last year
- A scikit-learn-compatible module for comparing imputation methods.☆137Updated 2 weeks ago
- For calculating global feature importance using Shapley values.☆267Updated this week
- Benchmarking synthetic data generation methods.☆272Updated last week
- Repository for CARTE: Context-Aware Representation of Table Entries☆119Updated 2 weeks ago
- Official git for "CTAB-GAN: Effective Table Data Synthesizing"☆85Updated last year
- Doubt your data, find bad labels.☆511Updated 9 months ago
- Data-SUITE: Data-centric identification of in-distribution incongruous examples (ICML 2022)☆10Updated 2 years ago
- Generating Tabular Synthetic Data using State of the Art GAN architecture☆79Updated 4 years ago