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.
- Timeseries efficacy metrics - Issue #35 by @csala
- Timeseries detection metrics - Issue #34 by @csala
- Ensure binary classification targets are bool - Issue #33 by @csala
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
Patch release to relax dependencies and avoid conflicts when using the latest SDV version.
Fix error on detection metrics when input data contains infinity or NaN values.
- ValueError: Input contains infinity or a value too large for dtype('float64') - Issue #11 by @csala
Add support for Python 3.8 and a broader range of dependencies.
First release to PyPI.