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CHANGELOG.md

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Changelog

1.1.4 - (2024-01-08)

Other changes:

  • Manually set compilation target in Makevars of the R-package based on the environment variable TARGET to simplify cross-compilation.

1.1.3 - (2024-01-06)

Other changes:

  • Update the extendr architecture for the package build. Thanks @JosiahParry!

1.1.2 - (2024-01-02)

Other changes:

  • Upgraded extendr-api and ndarray dependencies in R package.

1.1.1 - (2023-10-03)

Other changes:

  • Upgraded pyo3 dependency in Python package.

1.1.0 - (2023-08-01)

New features:

  • New argument forbidden_segments (list or vector of 2-tuple) or None to Control. If not None, changeforest will not split on split points contained in segments (a, b] in forbidden_segments (rust and Python only). Thanks @enzbus!

1.0.1 - (2022-06-01)

Bug fixes:

  • Python macos images are now again correctly built on GitHub runners.

1.0.0 - (2022-05-30)

First major release. There have been no changes since the last release. The manuscript is to be published in JMLR.

0.7.2 - (2022-05-09)

Bug fixes:

  • Fixed bugs when plotting results created with method="change_in_mean" or segmentation="sbs" or "wbs" (Python).

0.7.1 - (2022-05-02)

Bug fixes:

  • Fixed a bug resulting in no tick-labels being shown on the x-axis when plotting a BinarySegmentationResult.

0.7.0 - (2022-04-08)

New features:

  • New plotting methods BinarySegmentationResult.plot and OptimizerResult.plot (Python).
  • New plotting methods plot.binary_segmentation_result and plot.binary_segmentation_result (R).
  • Expanded documentation (R).
  • The changeforest function now has default values method="random_forest" and segmentation="bs" (R).

0.6.1 - (2022-04-06)

Bug fixes:

  • Fixed a bug in the Python package when passing random_forest_max_features='sqrt' to Control.

0.6.0 - (2022-03-17)

Breaking changes:

  • The default value for model_selection_n_permutations is now 199.
  • The default value for model_selection_alpha is now 0.02.
  • The default value for minimal_gain_to_split, use in the change_in_mean setup, is now log(n) * (d + 1), motivated by the BIC and [1].
  • The value for minimal_gain_to_split no longer gets automatically multiplied by n.

[1] Yao, Y.-C. (1988). Estimating the number of change-points via Schwarz’ criterion. Statist. Probab. Lett. 6 181–189. MR0919373

0.5.1 - (2022-03-16)

Bug fixes:

  • The pseudo-permutation-test now correctly skips the first and last minimal_segment_length * n observations when calculating the permuted maximal gains.

Other changes:

  • The first three elements of the result.optimizer_result.gain_results returned by the two-step search are no longer sorted by their maximal gain.

0.5.0 - (2022-03-15)

Breaking changes:

  • The parameters random_forest_mtry and random_forest_n_trees of Control have been renamed to random_forest_max_features and random_forest_n_estimators.
  • The default value for random_forest_max_features now is floor(sqrt(d)).

New features:

  • The parameter random_forest_max_features now can be supplied with a fraction 0 < f < 1, an integer i>=1, None (Python, Rust) / NULL (R) and "sqrt". Then, for each split, repsectively floor(f d), i, d or floor(sqrt(d)) features are considered.

Other changes:

  • Bump biosphere dependency to 0.3.0

0.4.4 - (2022-02-22)

Other changes:

  • Bump biosphere dependency to 0.2.2.

0.4.3 - (2021-01-29)

Other changes:

  • The default value for Control.minimal_gain_to_split is now log(n_samples) * n_features / n_samples, motivated by the Bayesian information criterion (BIC).

0.4.2 - (2021-01-21)

Other changes:

  • The R-package now makes use of the latest version of libR-sys, enabling compilation for Apple silicon on conda-forge (#86).

Bug fixes:

  • Fixed a bug where passing Control() to changeforest in the Python package overwrote the default value for random_forest_max_depth to None. Default values for Control in the python package are now "default" (#87).

0.4.1 - (2021-01-13)

Bug fixes:

  • Upgrade biosphere to 0.2.1 fixing a bug in RandomForest (#84).

Other changes:

  • New parameter model_selection_n_permutations (#85).

0.4.0 - (2021-01-11)

New features:

  • changeforest now uses random forests from biosphere. This should be faster than smartcore used previously and supports parallelization (#82).

0.3.0 - (2021-12-15)

New features:

  • Implemented trait Display for BinarySegmentationResult. In Python str(result) now prints a pretty display (#77).

Other changes:

  • The TwoStepSearch algorithm now only uses valid guesses from split_candidates (#76).

Bug fixes:

  • (R only) The R6 class Control now gets correctly exported (#79).

0.2.1 - (2021-12-13)

Bug fixes:

  • (Python only) Parameters will now be correctly passed to changeforest via Control even if they have an incorrect data type (#67).
  • Fixed a bug where SBS would panic in cases with very small minimal segments lengths due to rounding (#70).
  • Fixed a bug in model selection that resulted in a higher type I error (#71).

0.2.0 - (2021-12-10)

New features:

  • The TwoStepSearch now uses three initial guesses, the 0.25, 0.5 and 0.75 quantiles of the segment, for the first step. The the best split corresponding to the highest maximal gain from the three guesses is used in the second step. The permutation test used for model selection has also been adjusted to be consistent (#65).

    This increases estimation performance for classifier-based methods, especially if used with standard binary segmentation, i.e. for changeforst_bs and changeforest_knn.

0.1.1 - (2021-11-25)

Other changes:

  • Added license file for compatability with conda-forge.