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Releases: MAIF/shapash

v1.5.0: A better estimation of Shapley values with ACV backend

27 Sep 08:36
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Features

Bug fixes

  • Fix Shapash Report bug when using multiclass (#223)
  • Fix an attribute in SmartExplainer object (#247)

v1.4.4 : patch release

19 Jul 14:58
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This release fixes bugs in the WebApp (#223)

v1.4.2: patch release

18 Jun 13:49
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  • Fixes a bug with required python version for installation

v1.4.1: patch release

18 Jun 11:18
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Bug fix :

  • Fix Shapash installation with python 3.9

v1.4.0: Sets of features and correlation plot

16 Jun 08:10
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  • Groups of features compatible with:
    • Features importance plot (#188)
    • Contribution plot (#188)
    • Local plot (#207)
    • WebApp (#203)
    • SmartPredictor (#212)
  • New tutorial to illustrate how to use groups of features (#211)
  • New plot : correlation plot (#210) used in the Shapash report
  • Added compatibility with python version 3.9

Shapash Report - Bug Fix

15 Apr 07:56
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Minor Release - bugs fixed:

  • Correlation exception
  • generate_report() - kernel_name parameter (Papermill kernel)

Shapash Report

13 Apr 17:09
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  • Standalone report (#137)
    Standalone HTML file that contains the following information :
    • General information about the project
    • Dataset description
    • Model library, parameters, and other specifications
    • Dataset analysis
    • Global explainability of the model
    • Model performance
  • Digit counter breaks on 0 (#156)
  • Switch from SmartPredictor to SmartExplainer (#132)

Interaction plot and new features for WebApp

10 Mar 09:10
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  • WebApp Features: Title (#118), sort features in mask (#117), run app without prediction (#135)
  • Interaction plot: Plot (#124), calculation of top interactions (#120, #122)
  • BugFix: Xgboost (#127), Pickle (#131, #133)

Python 3.8 support

16 Jan 12:35
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Merge pull request #98 from MAIF/feature/update_python_v38_v39

Support python 3.8

v1.0.1: Merge pull request #96 from MAIF/nbformat-update

13 Jan 09:14
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