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Diffprivlib v0.3 #18

Merged
merged 99 commits into from
Jun 26, 2020
Merged

Diffprivlib v0.3 #18

merged 99 commits into from
Jun 26, 2020

Commits on Jan 16, 2020

  1. Removing support for Python 3.4

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Commits on Jan 30, 2020

  1. Switching to Python 3.8 for pylint checks

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Commits on Apr 7, 2020

  1. Updating notebooks to use score method

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Commits on Apr 29, 2020

  1. Adding tests

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Commits on May 5, 2020

  1. Adding coverage check to travis

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Commits on May 6, 2020

  1. Adding Discrete Gaussian mechanism

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  2. Fixing test

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Commits on May 8, 2020

  1. Adding sensitivity and safe sampling of exp bernoulli

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  2. Test nits

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Commits on May 11, 2020

  1. Test nits

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Commits on May 12, 2020

  1. Adding first prototype of BudgetAccountant and tests

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  2. Adding tests to accountant

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  3. Make check_spend throw BudgetError if budget exceeded

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  4. Changing test filename to match existing

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  5. Adding change_accountant test, typo

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  6. Moving check_accountant to utils

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  7. Adding accountant to histograms

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  8. Adding missing docstring

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  9. Fixing LGTM alert, adding accountant test

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  10. Removing redundant epsilon and delta check

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  11. Consolidating slack checks

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  12. Refactoring BudgetAccountant and its implementation

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  13. Adding type-checker to check method

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  14. Adding a default accountant

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  15. Adding min_epsilon to mitigate against floating point rounding errors

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  16. Adding tests for BudgetAccountant and check_epsilon_delta

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  17. Adding support for with() statement in BudgetAccountant

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  18. Adding accounting to tools/utils

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  19. Adding accounting to models

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  20. Bypassing total() call in check() with infinite budget

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  21. Adding accountant notebook

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  22. Nits

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  23. Adding support for len()

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  24. Notebook typos

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  25. Updating documentation

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  26. Adding accountant repr and updating notebooks

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  27. Adding examples to docs

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  28. Updating notebook, thanks Beat

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  29. Adding Budget tuple

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  30. Updating notebook

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  31. Updating docs

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  32. Docs and other minors

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Commits on May 13, 2020

  1. Merge branch 'master' into dev 

    Conflicts:
	diffprivlib/models/naive_bayes.py
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  2. Fix for exponential

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    naoise-h committed May 13, 2020
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  3. Updating README and Python support

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  4. Now requires sklearn 0.22

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  5. Adding Accountant to readme

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  6. Updating joblib requirement

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Commits on May 14, 2020

  1. Fixing error messages from _check_bounds

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  2. Adding default sensitivity to Geometric, adding variance

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  3. Geometric: removing sensitivity check, adding variance unit tests

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Commits on May 15, 2020

  1. Refactoring _check_bounds and adding tests

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  2. Extra test

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Commits on May 18, 2020

  1. Refactoring bounds and check_bounds for models

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  2. Adding sum function

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    naoise-h committed May 18, 2020
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  3. Removing initial and where from sum

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  4. Standardising documentation

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Commits on May 19, 2020

  1. Updating README with new bounds format

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  2. Adding support for zero sensitivity to mechanisms

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  3. Adding zero sensitivity/inf epsilon support to Gaussian mechs

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  4. Adding nansum and documentation

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Commits on May 20, 2020

  1. First draft of Naive Bayes fix

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  2. Limiting spent_budget output for accountant repr

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Commits on May 21, 2020

  1. Changing mean/var mechanisms

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  2. Changing budget allocation, adding tests

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  3. Merge branch 'naive_bayes_fix' into dev

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Commits on May 22, 2020

  1. Adding clip_to_norm and clip_to_bounds, with implementations in models. 

    - All models now require bounds where they required range previously
- In models with a bounds parameter, the input array is clipped to those bounds before learning starts
- In models with a data_norm paramter, the input array is clipped to that norm before learning starts
- Various validation functions are now in a separate validation module
- Documentation and tests added for clip_to_norm and clip_to_bounds
- Correct array checks added to KMeans
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  2. Bug fix in PCA for infer_dimensions (sklearn 0.23 compatibility)

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  3. Adding test for PCA 'mle' components

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  4. Adding bounds check to standard scaler

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  5. Ensuring bounds are always exposed in linear regression

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  6. Updating notebooks

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  7. Refactoring check_bounds to support scalar or vector bounds only

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  8. mean, std and var now require bounds instead of range

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  9. Adding clip to mean/var

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  10. Updating accountant notebook

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Commits on May 25, 2020

  1. Adding support for non-numpy array-like for mean/var/std

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  2. Minor utils refactor

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  3. Documentation nits

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  4. Clipping outputs of tools/utils

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  5. Default separation of bounds to 0

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Commits on May 26, 2020

  1. Reordering checks in LogisticRegression

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  2. Updating status to beta and other minor changes

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  3. Minor changes to 30seconds notebook and readme

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  4. Replacing single-char variable names

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  5. LGTM fix

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  6. Removing support for out and ddof in tools; fix line length

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  7. Removing unused parameters

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Commits on May 27, 2020

  1. Updating LogisticRegression notebook

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Commits on May 28, 2020

  1. Making accountant attributes private

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Commits on Jun 2, 2020

  1. Switching to NotImplementedError for bias/variance

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  2. Minor fixes from Marco's review 

    - Naive Bayes error message consistency
- Correct reading of bounds from data in PCA
- None no longer permitted as input to check_bounds
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  3. Adding count_nonzero to tools

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Commits on Jun 10, 2020

  1. Minor changes from Stefano's review 

    - Parenthesis in Vector mechanism to enhance readibility
- Explaining use of new accountant in StandardScaler
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Commits on Jun 16, 2020

  1. Fixing Laplace variance bug for non-zero delta

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Commits on Jun 19, 2020

  1. Adding exploration notebook

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Commits on Jun 22, 2020

  1. Minor notebook change

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  2. Adding keepdims to count_nonzero in line with Numpy 1.19

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  3. Fix logistic_regression_path documentation, thanks Marco

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