v0.4.0

🏭💥 New algorithms and more breaking changes

Least core, group testing, fixes to parellization and more documentation.

What's Changed

• GH action to mark issues as stale PR #201
• Disabled caching of Utility values as well as repeated evaluations by default PR #211
• Test and officially support Python version 3.9 and 3.10 PR #208
• Breaking change: Introduces a class ValuationResult to gather and inspect results from all valuation algorithms PR #214
• Fixes bug in Influence calculation with multi-dimensional input and adds new example notebook PR #195
• Documentation improvements PR #238 and PR #216
• Breaking change: Passes the input to MapReduceJob at initialization, removes chunkify_inputs argument from MapReduceJob, removes n_runs argument from MapReduceJob, calls the parallel backend's put() method for each generated chunk in _chunkify(), renames ParallelConfig's num_workers attribute to n_local_workers, fixes a bug in MapReduceJob's chunkification when n_runs >= n_jobs, and defines a sequential parallel backend to run all jobs in the current thread PR #232
• New method: Implements exact and monte carlo Least Core for data valuation, adds from_arrays() class method to the Dataset and GroupedDataset classes, adds extra_values argument to ValuationResult, adds compute_removal_score() and compute_random_removal_score() helper functions PR #237
• New method: Group Testing Shapley for valuation, from Jia et al. 2019 PR #240
• Fixes bug in ray initialization in RayParallelBackend class PR #239
• Implements "Egalitarian Least Core", adds cvxpy as a dependency and uses it instead of scipy as optimizer PR #243
• Notebook on using influence functions for Convolutional NNs PR #195

Full Changelog: v0.3.0...v0.4.0

v0.3.0

💥 Breaking changes

• Simplified and fixed powerset sampling and testing PR #181
• Simplified and fixed publishing to PyPI from CI PR #183
• Fixed bug in release script and updated contributing docs PR #184
• Added Pull Request template PR #185
• Modified Pull Request template to automatically link PR to issue PR ##186
• First implementation of Owen Sampling, squashed scores, better testing PR #194
• Improved documentation on caching, Shapley, caveats of values, bibtex PR #194
• Breaking change: Rearranging of modules to accommodate for new methods PR #194

v0.2.0

What's Changed

• Improve adding Notebooks to the Documentation by @AnesBenmerzoug in #155
• Fix preview release creation in CI by @AnesBenmerzoug in #159
• Add more badges to readme by @AnesBenmerzoug in #162
• Fix catching of ConnectionRefusedError in caching by @mdbenito in #170
• Fix chunkification of data in MapReduceJob by @AnesBenmerzoug in #176
• Improvements to notebooks and API documentation by @mdbenito in #161
• Fixed a bug in random matrix generation by @mdbenito in #161

Plus several minor changes and refactoring.

Full Changelog: v0.1.0...v0.2.0

v0.1.0

This is the very first release of pyDVL 🎉

Features

• Data Valuation Methods:

  • Leave-One-Out
  • Influence Functions
  • Shapley:
    • Exact Permutation and Combinatorial
    • Montecarlo Permutation and Combinatorial
    • Truncated Montecarlo Permutation

• Caching of results with Memcached

• Parallelization of computations with Ray

• Documentation

• Notebooks containing examples of different use cases

If you find any bugs while using it, please feel free to open an issue.

Contributors: @AnesBenmerzoug,@mdbenito, @kosmitive, @Xuzzo

Full Changelog: https://github.com/appliedAI-Initiative/pyDVL/commits/v0.1.0