v1.0.0 release candiate 0

What's Changed

• DOC exclude test directories in gen_reg_pages.py by @lorentzenchr in #68
• MNT update to polars 0.17.2 by @lorentzenchr in #73
• MNT update mkdocs-material 9.1 and mkdocs-jupyter 0.24 by @lorentzenchr in #70
• ENH add generalized PAVA for isotonic regression by @lorentzenchr in #74
• ENH add IsotonicRegression class by @lorentzenchr in #78
• ENH add quantile to reliability diagram by @lorentzenchr in #79
• ENH add quantiles and expectile to scoring.decompose by @lorentzenchr in #81
• MNT update gitignore excluding some ipynb by @lorentzenchr in #82
• MNT update dependencies by @lorentzenchr in #83
• CI add monthly run of test matrix by @lorentzenchr in #84
• MNT deploy docs on release instread of on push by @lorentzenchr in #85
• MNT increase mypy to version 1.4 by @lorentzenchr in #86
• ENH add confidence_level to plot_bias by @lorentzenchr in #87
• ENH support multiple y_pred models in scoring.decompose by @lorentzenchr in #88
• DOC add quantile regression example by @lorentzenchr in #91
• DOC extend readme and index by @lorentzenchr in #93
• REL increase to version 1.0.0rc0 by @lorentzenchr in #92

Full Changelog: v0.2.0...v1.0.0rc0

v0.2.0

What's Changed

• DOC hyperlink in highlights of frontpage by @lorentzenchr in #46
• CI codecov setup by @lorentzenchr in #47
• DOC add codecov badge by @lorentzenchr in #48
• DOC add link to release notes by @lorentzenchr in #49
• MNT add .codecov.yml by @lorentzenchr in #50
• TST add test_compute_bias_1d_array_like by @lorentzenchr in #51
• CI upload coverage report only once by @lorentzenchr in #52
• FIX p-value when stderr is zero but bias_count>=2 by @lorentzenchr in #54
• ENH keep null values in compute_bias for low n_bins by @lorentzenchr in #53
• DOC add trunk-based development by @lorentzenchr in #55
• DOC fix typos by @mayer79 in #56
• FIX account for Null value when binning in compute_bias by @lorentzenchr in #57
• FIX fix logic for string features with n_bins in compute_bias by @lorentzenchr in #58
• ENH plot null values in plot_bias by @lorentzenchr in #59
• ENH add ElementaryScore by @lorentzenchr in #60
• FIX ElementaryScore always non-negative by @lorentzenchr in #62
• ENH add plot_murphy_diagram by @lorentzenchr in #63
• ENH plot_bias with Null values by @lorentzenchr in #65
• DOC add Murphy plot to regression example by @lorentzenchr in #66
• REL increase to version 0.2.0 by @lorentzenchr in #67

New Contributors

• @mayer79 made their first contribution in #56

Full Changelog: v0.1.1...v0.2.0

v0.1.1

Enhancements:

• Support NaN and Null in compute_bias (PR #43)

Bug Fixes:

• Always output column "bias_weights" in compute_bias (PR #44)

v0.1.0

Some highlights:

• Confidence intervals for plot_reliability_diagram via arguments n_bootstrap and confidence_level (PR #32).
• New option diagram_type = "bias" for plot_reliability_diagram, which is roughly a 45 degree rotated plot (PR #35).
• Better visualisation of uncertainty/standard errors in plot_bias and distinction between numerical and categorical features (PR #37).
• Consistently sorted output, i.e. the different (model) columns of y_pred (PR #37).
• Number of effective (output) bins is now always at most n_bins in compute_bias and plot_bias (PR #37).
• Switch to ruff (PR #34)

v0.0.3

A new module scoring containing:

• Add strictly consistent, homogeneous scoring functions
  • HomogeneousExpectileScore for mean an expectiles
  • HomogeneousQuantileScore for quantiles
  • SquaredError, PoissonDeviance, GammaDeviance and PinballLoss for convenience
• Add LogLoss
• Add score decomposition decompose 🚀
  To my knowledge, this is the first time the score decomposition into miscalibration, discrimination (or resolution) is available in Python. R users can use the wonderful reliabilitydiag package of @aijordan for quite some time now.

v0.0.2

• Added support for case weights.
• Use of the fantastic https://www.pola.rs/ library (instead of pyarrow and pandas).

v0.0.1

First public release