v0.3.1 - 2021-07-12

v0.3.1 - 2021-07-12

This release fixes a bug to make the privacy metrics available in the API docs.
It also updates dependencies to ensure compatibility with the rest of the SDV ecosystem.

Issues closed

• CategoricalSVM not being imported - Issue #65 by @csala

v0.3.0 - 2021-03-31

This release includes privacy metrics to evaluate if the real data could be obtained or deduced from the synthetic samples. Additionally all the metrics have a normalize method which takes the raw_score generated by the metric and returns a value between 0 and 1.

Issues closed

• Add normalize method to metrics - Issue #51 by @csala and @fealho
• Implement privacy metrics - Issue #36 by @ZhuofanXie and @fealho

v0.2.0 - 2021-02-24

Dependency upgrades to ensure compatibility with the rest of the SDV ecosystem.

v0.1.3 - 2021-02-13

Updates the required dependecies to facilitate a conda release.

Issues closed

• Upgrade sktime - Issue #49 by @fealho

v0.1.2 - 2021-01-27

Big fixing release that addresses several minor errors.

Issues closed

• More splits than classes - Issue #46 by @fealho
• Scipy 1.6.0 causes an AttributeError - Issue #44 by @fealho
• Time series metrics fails with variable length timeseries - Issue #42 by @fealho
• ParentChildDetection metrics KeyError - Issue #39 by @csala

v0.1.1 - 2020-12-30

This version adds Time Series Detection and Efficacy metrics, as well as a fix
to ensure that Single Table binary classification efficacy metrics work well
with binary targets which are not boolean.

Issues closed

• Timeseries efficacy metrics - Issue #35 by @csala
• Timeseries detection metrics - Issue #34 by @csala
• Ensure binary classification targets are bool - Issue #33 by @csala

v0.1.0 - 2020-12-18

This release introduces a new project organization and API, with metrics
grouped by data modality, with a common API:

• Single Column
• Column Pair
• Single Table
• Multi Table
• Time Series

Within each data modality, different families of metrics have been implemented:

• Statistical
• Detection
• Bayesian Network and Gaussian Mixture Likelihood
• Machine Learning Efficacy

v0.0.4 - 2020-11-27

Patch release to relax dependencies and avoid conflicts when using the latest SDV version.

v0.0.3 - 2020-11-20

Fix error on detection metrics when input data contains infinity or NaN values.

Issues closed

• ValueError: Input contains infinity or a value too large for dtype('float64') - Issue #11 by @csala

v0.0.2 - 2020-08-08

Add support for Python 3.8 and a broader range of dependencies.