Overview — Shapash 2.7.9 documentation
Shapash works for Regression, Binary Classification or Multiclass problems. It is compatible with many models: Catboost, Xgboost, LightGBM, Sklearn Ensemble, Linear models and SVM.
Welcome to Shapash’s documentation ! — Shapash 2.7.9 …
Shapash is a Python library designed to make machine learning interpretable and accessible to everyone. It offers various visualization types with clear and explicit labels that are easy to understand.
Installation instructions — Shapash 2.7.9 documentation
When using Shapash, you may encounter some compatibility issues related to your environment and the libraries’ versions used. The extras requirements of Shapash allow you to update your …
Tutorials — Shapash 2.7.9 documentation
Tutorials This part offers a series of tutorials and allows users to gradually discover the different features of Shapash
Start the Shapash Web App on a sample dataset
With this tutorial you: Understand how shapash works with a simple use case Start WebApp to understand your model and save these results Contents: - Build a Regressor - Compile Shapash SmartExplainer - Start Shapash WebApp - Export synt with to_pandas function - Save Shapash object in pickle file
Shapash in Jupyter - Overview — Shapash 2.7.9 documentation
Shapash in Jupyter - Overview With this tutorial you: Understand how Shapash works in Jupyter Notebook with a simple use case Contents: - Build a Regressor - Compile Shapash SmartExplainer - Display global and local explanability - Export local summarized explainability with to_pandas method - Save Shapash object in pickle file
shapash.explainer.smart_explainer — Shapash 2.7.9 documentation
Shapash lets users define their own probability values y_target : pandas.Series or pandas.DataFrame, optional (default: None) Target values (1 column only). The index must be identical to the index of x_init.
SmartExplainer Object — Shapash 2.7.9 documentation
The Plot Methods class shapash.explainer.smart_plotter.SmartPlotter(explainer, colors_dict=None)[source] ¶ Bases: object SmartPlotter is a Bridge pattern decoupling plotting functions from SmartExplainer.
Shapash Report — Shapash 2.7.8 documentation
The Shapash Report feature allows data scientists to deliver to anyone who is interested in their project a document that freezes different aspects of their work as a basis of an audit report.
overview — Shapash 2.7.9 documentation
Start the Shapash Web App on a sample dataset Shapash in Jupyter - Overview Shapash model in production - Overview