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authorCoprDistGit <infra@openeuler.org>2023-04-25 05:17:24 +0000
committerCoprDistGit <infra@openeuler.org>2023-04-25 05:17:24 +0000
commit5b42075c52dcd18d56d37f51463aefbcd143e32b (patch)
tree5de6fb5fb8006c781a3fd589542356e1f0391a29
parentb37aa26f2169a66a8a883b2c7689d40420034e59 (diff)
automatic import of python-shapashopeneuler20.03
-rw-r--r--.gitignore1
-rw-r--r--python-shapash.spec65
-rw-r--r--sources2
3 files changed, 42 insertions, 26 deletions
diff --git a/.gitignore b/.gitignore
index b9e8014..e876da7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,2 @@
/shapash-2.3.0.tar.gz
+/shapash-2.3.2.tar.gz
diff --git a/python-shapash.spec b/python-shapash.spec
index 0f9637f..5ab3e12 100644
--- a/python-shapash.spec
+++ b/python-shapash.spec
@@ -1,11 +1,11 @@
%global _empty_manifest_terminate_build 0
Name: python-shapash
-Version: 2.3.0
+Version: 2.3.2
Release: 1
Summary: Shapash is a Python library which aims to make machine learning interpretable and understandable by everyone.
License: Apache Software License 2.0
URL: https://github.com/MAIF/shapash
-Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d0/32/7258852e772286c39e9f610833f869a5a1acafe457fffff834a9048dea12/shapash-2.3.0.tar.gz
+Source0: https://mirrors.nju.edu.cn/pypi/web/packages/9b/f0/6a638eb01670477ef85038500791ba23fdc9742b856fa79a182ebb2ae8e2/shapash-2.3.2.tar.gz
BuildArch: noarch
Requires: python3-plotly
@@ -76,16 +76,16 @@ Requires: python3-xgboost
| Version | New Feature | Description | Tutorial |
|:-------------:|:-------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------:|:--------:|
-| 2.3.x | Additional dataset columns <br> (Demo coming soon) | In Webapp: Target and error columns added to dataset and possibility to add features outside the model for more filtering options | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/add_column_icon.png" width="50" title="add_column">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
-| 2.3.x | Identity card <br> (Demo coming soon) | In Webapp: New identity card to summarize the information of the selected sample | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/identity_card.png" width="50" title="identity">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
-| 2.2.x | Picking samples <br> [New demo](https://shapash-demo.ossbymaif.fr/) | New tab in the webapp for picking samples. The graph represents the "True Values Vs Predicted Values" | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/picking.png" width="50" title="picking">](https://github.com/MAIF/shapash/blob/master/tutorial/plot/tuto-plot06-prediction_plot.ipynb)
-| 2.2.x | Dataset Filter <br> [New demo](https://shapash-demo.ossbymaif.fr/) | New tab in the webapp to filter data. And several improvements in the webapp: subtitles, labels, screen adjustments | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/webapp.png" width="50" title="webapp">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
+| 2.3.x | Additional dataset columns <br> [New demo](https://shapash-demo.ossbymaif.fr/) <br> [Article](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb) | In Webapp: Target and error columns added to dataset and possibility to add features outside the model for more filtering options | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/add_column_icon.png" width="50" title="add_column">](https://github.com/MAIF/shapash/blob/master/tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+| 2.3.x | Identity card <br> [New demo](https://shapash-demo.ossbymaif.fr/) <br> [Article](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb) | In Webapp: New identity card to summarize the information of the selected sample | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/identity_card.png" width="50" title="identity">](https://github.com/MAIF/shapash/blob/master/tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+| 2.2.x | Picking samples <br> [Article](https://www.kdnuggets.com/2022/11/picking-examples-understand-machine-learning-model.html) | New tab in the webapp for picking samples. The graph represents the "True Values Vs Predicted Values" | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/picking.png" width="50" title="picking">](https://github.com/MAIF/shapash/blob/master/tutorial/plot/tuto-plot06-prediction_plot.ipynb)
+| 2.2.x | Dataset Filter <br> | New tab in the webapp to filter data. And several improvements in the webapp: subtitles, labels, screen adjustments | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/webapp.png" width="50" title="webapp">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
| 2.0.x | Refactoring Shapash <br> | Refactoring attributes of compile methods and init. Refactoring implementation for new backends | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/modular.png" width="50" title="modular">](https://github.com/MAIF/shapash/blob/master/tutorial/backend/tuto-backend-01.ipynb)
| 1.7.x | Variabilize Colors <br> | Giving possibility to have your own colour palette for outputs adapted to your design | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/variabilize-colors.png" width="50" title="variabilize-colors">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common02-colors.ipynb)
-| 1.6.x | Explainability Quality Metrics <br> [article](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514) | To help increase confidence in explainability methods, you can evaluate the relevance of your explainability using 3 metrics: **Stability**, **Consistency** and **Compacity** | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/quality-metrics.png" width="50" title="quality-metrics">](https://github.com/MAIF/shapash/blob/master/tutorial/explainability_quality/tuto-quality01-Builing-confidence-explainability.ipynb)
+| 1.6.x | Explainability Quality Metrics <br> [Article](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514) | To help increase confidence in explainability methods, you can evaluate the relevance of your explainability using 3 metrics: **Stability**, **Consistency** and **Compacity** | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/quality-metrics.png" width="50" title="quality-metrics">](https://github.com/MAIF/shapash/blob/master/tutorial/explainability_quality/tuto-quality01-Builing-confidence-explainability.ipynb)
| 1.5.x | ACV Backend <br> | A new way of estimating Shapley values using ACV. [More info about ACV here](https://towardsdatascience.com/the-right-way-to-compute-your-shapley-values-cfea30509254). | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/wheel.png" width="50" title="wheel-acv-backend">](tutorial/explainer/tuto-expl03-Shapash-acv-backend.ipynb) |
-| 1.4.x | Groups of features <br> [demo](https://shapash-demo2.ossbymaif.fr/) | You can now regroup features that share common properties together. <br>This option can be useful if your model has a lot of features. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/groups_features.gif" width="120" title="groups-features">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common01-groups_of_features.ipynb) |
-| 1.3.x | Shapash Report <br> [demo](https://shapash.readthedocs.io/en/latest/report.html) | A standalone HTML report that constitutes a basis of an audit document. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/report-icon.png" width="50" title="shapash-report">](https://github.com/MAIF/shapash/blob/master/tutorial/report/tuto-shapash-report01.ipynb) |
+| 1.4.x | Groups of features <br> [Demo](https://shapash-demo2.ossbymaif.fr/) | You can now regroup features that share common properties together. <br>This option can be useful if your model has a lot of features. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/groups_features.gif" width="120" title="groups-features">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common01-groups_of_features.ipynb) |
+| 1.3.x | Shapash Report <br> [Demo](https://shapash.readthedocs.io/en/latest/report.html) | A standalone HTML report that constitutes a basis of an audit document. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/report-icon.png" width="50" title="shapash-report">](https://github.com/MAIF/shapash/blob/master/tutorial/report/tuto-shapash-report01.ipynb) |
## 🔍 Overview
@@ -105,6 +105,7 @@ Shapash also contributes to data science auditing by displaying usefull informat
- [Group of features - Towards AI](https://pub.towardsai.net/machine-learning-6011d5d9a444)
- [Building confidence on explainability - Towards DS](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514)
- [Picking Examples to Understand Machine Learning Model](https://www.kdnuggets.com/2022/11/picking-examples-understand-machine-learning-model.html)
+ - [Enhancing Webapp Built-In Features for Comprehensive Machine Learning Model Interpretation](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb)
<p align="center">
@@ -343,7 +344,11 @@ This github repository offers many tutorials to allow you to easily get started
</details>
+<details><summary><b>Analysing your model via Shapash WebApp</b> </summary>
+- [Add features outside of the model for more exploration options](tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+
+</details>
%package -n python3-shapash
@@ -390,16 +395,16 @@ BuildRequires: python3-pip
| Version | New Feature | Description | Tutorial |
|:-------------:|:-------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------:|:--------:|
-| 2.3.x | Additional dataset columns <br> (Demo coming soon) | In Webapp: Target and error columns added to dataset and possibility to add features outside the model for more filtering options | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/add_column_icon.png" width="50" title="add_column">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
-| 2.3.x | Identity card <br> (Demo coming soon) | In Webapp: New identity card to summarize the information of the selected sample | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/identity_card.png" width="50" title="identity">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
-| 2.2.x | Picking samples <br> [New demo](https://shapash-demo.ossbymaif.fr/) | New tab in the webapp for picking samples. The graph represents the "True Values Vs Predicted Values" | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/picking.png" width="50" title="picking">](https://github.com/MAIF/shapash/blob/master/tutorial/plot/tuto-plot06-prediction_plot.ipynb)
-| 2.2.x | Dataset Filter <br> [New demo](https://shapash-demo.ossbymaif.fr/) | New tab in the webapp to filter data. And several improvements in the webapp: subtitles, labels, screen adjustments | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/webapp.png" width="50" title="webapp">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
+| 2.3.x | Additional dataset columns <br> [New demo](https://shapash-demo.ossbymaif.fr/) <br> [Article](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb) | In Webapp: Target and error columns added to dataset and possibility to add features outside the model for more filtering options | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/add_column_icon.png" width="50" title="add_column">](https://github.com/MAIF/shapash/blob/master/tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+| 2.3.x | Identity card <br> [New demo](https://shapash-demo.ossbymaif.fr/) <br> [Article](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb) | In Webapp: New identity card to summarize the information of the selected sample | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/identity_card.png" width="50" title="identity">](https://github.com/MAIF/shapash/blob/master/tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+| 2.2.x | Picking samples <br> [Article](https://www.kdnuggets.com/2022/11/picking-examples-understand-machine-learning-model.html) | New tab in the webapp for picking samples. The graph represents the "True Values Vs Predicted Values" | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/picking.png" width="50" title="picking">](https://github.com/MAIF/shapash/blob/master/tutorial/plot/tuto-plot06-prediction_plot.ipynb)
+| 2.2.x | Dataset Filter <br> | New tab in the webapp to filter data. And several improvements in the webapp: subtitles, labels, screen adjustments | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/webapp.png" width="50" title="webapp">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
| 2.0.x | Refactoring Shapash <br> | Refactoring attributes of compile methods and init. Refactoring implementation for new backends | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/modular.png" width="50" title="modular">](https://github.com/MAIF/shapash/blob/master/tutorial/backend/tuto-backend-01.ipynb)
| 1.7.x | Variabilize Colors <br> | Giving possibility to have your own colour palette for outputs adapted to your design | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/variabilize-colors.png" width="50" title="variabilize-colors">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common02-colors.ipynb)
-| 1.6.x | Explainability Quality Metrics <br> [article](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514) | To help increase confidence in explainability methods, you can evaluate the relevance of your explainability using 3 metrics: **Stability**, **Consistency** and **Compacity** | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/quality-metrics.png" width="50" title="quality-metrics">](https://github.com/MAIF/shapash/blob/master/tutorial/explainability_quality/tuto-quality01-Builing-confidence-explainability.ipynb)
+| 1.6.x | Explainability Quality Metrics <br> [Article](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514) | To help increase confidence in explainability methods, you can evaluate the relevance of your explainability using 3 metrics: **Stability**, **Consistency** and **Compacity** | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/quality-metrics.png" width="50" title="quality-metrics">](https://github.com/MAIF/shapash/blob/master/tutorial/explainability_quality/tuto-quality01-Builing-confidence-explainability.ipynb)
| 1.5.x | ACV Backend <br> | A new way of estimating Shapley values using ACV. [More info about ACV here](https://towardsdatascience.com/the-right-way-to-compute-your-shapley-values-cfea30509254). | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/wheel.png" width="50" title="wheel-acv-backend">](tutorial/explainer/tuto-expl03-Shapash-acv-backend.ipynb) |
-| 1.4.x | Groups of features <br> [demo](https://shapash-demo2.ossbymaif.fr/) | You can now regroup features that share common properties together. <br>This option can be useful if your model has a lot of features. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/groups_features.gif" width="120" title="groups-features">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common01-groups_of_features.ipynb) |
-| 1.3.x | Shapash Report <br> [demo](https://shapash.readthedocs.io/en/latest/report.html) | A standalone HTML report that constitutes a basis of an audit document. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/report-icon.png" width="50" title="shapash-report">](https://github.com/MAIF/shapash/blob/master/tutorial/report/tuto-shapash-report01.ipynb) |
+| 1.4.x | Groups of features <br> [Demo](https://shapash-demo2.ossbymaif.fr/) | You can now regroup features that share common properties together. <br>This option can be useful if your model has a lot of features. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/groups_features.gif" width="120" title="groups-features">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common01-groups_of_features.ipynb) |
+| 1.3.x | Shapash Report <br> [Demo](https://shapash.readthedocs.io/en/latest/report.html) | A standalone HTML report that constitutes a basis of an audit document. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/report-icon.png" width="50" title="shapash-report">](https://github.com/MAIF/shapash/blob/master/tutorial/report/tuto-shapash-report01.ipynb) |
## 🔍 Overview
@@ -419,6 +424,7 @@ Shapash also contributes to data science auditing by displaying usefull informat
- [Group of features - Towards AI](https://pub.towardsai.net/machine-learning-6011d5d9a444)
- [Building confidence on explainability - Towards DS](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514)
- [Picking Examples to Understand Machine Learning Model](https://www.kdnuggets.com/2022/11/picking-examples-understand-machine-learning-model.html)
+ - [Enhancing Webapp Built-In Features for Comprehensive Machine Learning Model Interpretation](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb)
<p align="center">
@@ -657,7 +663,11 @@ This github repository offers many tutorials to allow you to easily get started
</details>
+<details><summary><b>Analysing your model via Shapash WebApp</b> </summary>
+
+- [Add features outside of the model for more exploration options](tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+</details>
%package help
@@ -701,16 +711,16 @@ Provides: python3-shapash-doc
| Version | New Feature | Description | Tutorial |
|:-------------:|:-------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------------------------------:|:--------:|
-| 2.3.x | Additional dataset columns <br> (Demo coming soon) | In Webapp: Target and error columns added to dataset and possibility to add features outside the model for more filtering options | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/add_column_icon.png" width="50" title="add_column">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
-| 2.3.x | Identity card <br> (Demo coming soon) | In Webapp: New identity card to summarize the information of the selected sample | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/identity_card.png" width="50" title="identity">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
-| 2.2.x | Picking samples <br> [New demo](https://shapash-demo.ossbymaif.fr/) | New tab in the webapp for picking samples. The graph represents the "True Values Vs Predicted Values" | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/picking.png" width="50" title="picking">](https://github.com/MAIF/shapash/blob/master/tutorial/plot/tuto-plot06-prediction_plot.ipynb)
-| 2.2.x | Dataset Filter <br> [New demo](https://shapash-demo.ossbymaif.fr/) | New tab in the webapp to filter data. And several improvements in the webapp: subtitles, labels, screen adjustments | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/webapp.png" width="50" title="webapp">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
+| 2.3.x | Additional dataset columns <br> [New demo](https://shapash-demo.ossbymaif.fr/) <br> [Article](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb) | In Webapp: Target and error columns added to dataset and possibility to add features outside the model for more filtering options | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/add_column_icon.png" width="50" title="add_column">](https://github.com/MAIF/shapash/blob/master/tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+| 2.3.x | Identity card <br> [New demo](https://shapash-demo.ossbymaif.fr/) <br> [Article](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb) | In Webapp: New identity card to summarize the information of the selected sample | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/identity_card.png" width="50" title="identity">](https://github.com/MAIF/shapash/blob/master/tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+| 2.2.x | Picking samples <br> [Article](https://www.kdnuggets.com/2022/11/picking-examples-understand-machine-learning-model.html) | New tab in the webapp for picking samples. The graph represents the "True Values Vs Predicted Values" | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/picking.png" width="50" title="picking">](https://github.com/MAIF/shapash/blob/master/tutorial/plot/tuto-plot06-prediction_plot.ipynb)
+| 2.2.x | Dataset Filter <br> | New tab in the webapp to filter data. And several improvements in the webapp: subtitles, labels, screen adjustments | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/webapp.png" width="50" title="webapp">](https://github.com/MAIF/shapash/blob/master/tutorial/tutorial01-Shapash-Overview-Launch-WebApp.ipynb)
| 2.0.x | Refactoring Shapash <br> | Refactoring attributes of compile methods and init. Refactoring implementation for new backends | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/modular.png" width="50" title="modular">](https://github.com/MAIF/shapash/blob/master/tutorial/backend/tuto-backend-01.ipynb)
| 1.7.x | Variabilize Colors <br> | Giving possibility to have your own colour palette for outputs adapted to your design | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/variabilize-colors.png" width="50" title="variabilize-colors">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common02-colors.ipynb)
-| 1.6.x | Explainability Quality Metrics <br> [article](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514) | To help increase confidence in explainability methods, you can evaluate the relevance of your explainability using 3 metrics: **Stability**, **Consistency** and **Compacity** | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/quality-metrics.png" width="50" title="quality-metrics">](https://github.com/MAIF/shapash/blob/master/tutorial/explainability_quality/tuto-quality01-Builing-confidence-explainability.ipynb)
+| 1.6.x | Explainability Quality Metrics <br> [Article](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514) | To help increase confidence in explainability methods, you can evaluate the relevance of your explainability using 3 metrics: **Stability**, **Consistency** and **Compacity** | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/quality-metrics.png" width="50" title="quality-metrics">](https://github.com/MAIF/shapash/blob/master/tutorial/explainability_quality/tuto-quality01-Builing-confidence-explainability.ipynb)
| 1.5.x | ACV Backend <br> | A new way of estimating Shapley values using ACV. [More info about ACV here](https://towardsdatascience.com/the-right-way-to-compute-your-shapley-values-cfea30509254). | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/wheel.png" width="50" title="wheel-acv-backend">](tutorial/explainer/tuto-expl03-Shapash-acv-backend.ipynb) |
-| 1.4.x | Groups of features <br> [demo](https://shapash-demo2.ossbymaif.fr/) | You can now regroup features that share common properties together. <br>This option can be useful if your model has a lot of features. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/groups_features.gif" width="120" title="groups-features">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common01-groups_of_features.ipynb) |
-| 1.3.x | Shapash Report <br> [demo](https://shapash.readthedocs.io/en/latest/report.html) | A standalone HTML report that constitutes a basis of an audit document. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/report-icon.png" width="50" title="shapash-report">](https://github.com/MAIF/shapash/blob/master/tutorial/report/tuto-shapash-report01.ipynb) |
+| 1.4.x | Groups of features <br> [Demo](https://shapash-demo2.ossbymaif.fr/) | You can now regroup features that share common properties together. <br>This option can be useful if your model has a lot of features. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/groups_features.gif" width="120" title="groups-features">](https://github.com/MAIF/shapash/blob/master/tutorial/common/tuto-common01-groups_of_features.ipynb) |
+| 1.3.x | Shapash Report <br> [Demo](https://shapash.readthedocs.io/en/latest/report.html) | A standalone HTML report that constitutes a basis of an audit document. | [<img src="https://raw.githubusercontent.com/MAIF/shapash/master/docs/_static/report-icon.png" width="50" title="shapash-report">](https://github.com/MAIF/shapash/blob/master/tutorial/report/tuto-shapash-report01.ipynb) |
## 🔍 Overview
@@ -730,6 +740,7 @@ Shapash also contributes to data science auditing by displaying usefull informat
- [Group of features - Towards AI](https://pub.towardsai.net/machine-learning-6011d5d9a444)
- [Building confidence on explainability - Towards DS](https://towardsdatascience.com/building-confidence-on-explainability-methods-66b9ee575514)
- [Picking Examples to Understand Machine Learning Model](https://www.kdnuggets.com/2022/11/picking-examples-understand-machine-learning-model.html)
+ - [Enhancing Webapp Built-In Features for Comprehensive Machine Learning Model Interpretation](https://pub.towardsai.net/shapash-2-3-0-comprehensive-model-interpretation-40b50157c2fb)
<p align="center">
@@ -968,11 +979,15 @@ This github repository offers many tutorials to allow you to easily get started
</details>
+<details><summary><b>Analysing your model via Shapash WebApp</b> </summary>
+
+- [Add features outside of the model for more exploration options](tutorial/webapp/tuto-webapp01-additional-data.ipynb)
+</details>
%prep
-%autosetup -n shapash-2.3.0
+%autosetup -n shapash-2.3.2
%build
%py3_build
@@ -1012,5 +1027,5 @@ mv %{buildroot}/doclist.lst .
%{_docdir}/*
%changelog
-* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 2.3.0-1
+* Tue Apr 25 2023 Python_Bot <Python_Bot@openeuler.org> - 2.3.2-1
- Package Spec generated
diff --git a/sources b/sources
index 0d901d8..3ccc57f 100644
--- a/sources
+++ b/sources
@@ -1 +1 @@
-cc3ca82be59056d0bdd811bdb172478b shapash-2.3.0.tar.gz
+84c18f3cecd7768e4895919f9f6da73d shapash-2.3.2.tar.gz