explainerdashboard
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
파일 탐색기
최종 버전 다운로드 (.zip)- codecov.yml
- explainerdashboard.yml
- upload_to_pypi.yml
- FUNDING.yml
- .DS_Store
- bootstrap.min.css
- dash_bootstrap_components.min.js
- stylesheet.css
- classification.png
- classifier_index.png
- classifier_prediction.png
- confusion_matrix.png
- contribs_graph.png
- contribs_table.png
- cumulative_lift.png
- feature_descriptions.png
- feature_input.png
- importances.png
- index_clas.png
- interaction_summary.png
- lift_curve.png
- pdp.png
- poslabel_selector.png
- pr_auc.png
- precision.png
- pred_summary_clas.png
- pred_summary_reg.png
- pred_vs_actual.png
- reg_vs_col.png
- regression_index.png
- regression_prediction.png
- residuals.png
- residuals_vs_col.png
- roc_auc.png
- shap_dependence.png
- shap_dependence_cats.png
- shap_interaction.png
- shap_summary.png
- shap_summary_detailed.png
- tree_table.png
- tree_viz.png
- trees.png
- whatif.png
- xgb_trees.png
- custom.png
- custom_dashboard.gif
- custom_dashboard.png
- explainerhub.png
- flatlytheme.png
- heroku_buildpack.png
- inline_example.png
- inline_screenshot.gif
- inline_screenshot.png
- notebook_screenshot.png
- screenshot.gif
- screenshot.png
- simple_classifier_dashboard.png
- simple_regression_dashboard.png
- tab_decision_trees.png
- tab_feature_dependence.png
- tab_importances.png
- tab_individual_predictions.png
- tab_interactions.png
- tab_model_performance.png
- tab_whatif.png
- buildcustom.rst
- cli.rst
- components.rst
- conf.py
- custom.rst
- dashboards.rst
- deployment.rst
- explainers.rst
- help.rst
- hub.rst
- index.rst
- inline.rst
- license.rst
- tabs.rst
- make.bat
- Makefile
- requirements.txt
- bootstrap.min.css
- favicon.ico
- __init__.py
- classifier_components.py
- composites.py
- connectors.py
- decisiontree_components.py
- overview_components.py
- regression_components.py
- shap_components.py
- titanic_test.csv
- titanic_train.csv
- bootstrap.min.css
- bootstrap.min.js
- favicon.ico
- __init__.py
- cli.py
- custom.py
- dashboard_methods.py
- dashboards.py
- datasets.py
- explainer_methods.py
- explainer_plots.py
- explainers.py
- to_html.py
- custom_examples.ipynb
- dashboard_examples.ipynb
- explainer_examples.ipynb
- simplified_classifier_dashboard_example.ipynb
- run_lgbm_dashboard.py
- __init__.py
- test_hub.py
- test_hub_cli.py
- test_hub_integration.py
- __init__.py
- conftest.py
- test_customdashboards.py
- test_dashboards.py
- data.csv
- pipeline_data.csv
- __init__.py
- conftest.py
- test_boosting_models.py
- test_catboost_classifier.py
- test_catboost_regression.py
- test_categorical_sorting.py
- test_classifier_base.py
- test_classifier_explainer.py
- test_cli.py
- test_cv.py
- test_dashboard_dumps.py
- test_datasets.py
- test_decisiontrees.py
- test_dtreeviz_contracts.py
- test_dtype_alignment.py
- test_explainer_methods.py
- test_externalsource.py
- test_feature_input_component.py
- test_lgbm_string_categoricals.py
- test_linear_model.py
- test_multiclass.py
- test_njobs.py
- test_pipelines.py
- test_randomforest_explainer.py
- test_regression_base.py
- test_regression_explainer.py
- test_save_html_custom_tab.py
- test_skorch_models.py
- test_xgboost_treeviz.py
- .gitattributes
- .gitignore
- .pre-commit-config.yaml
- .readthedocs.yml
- conftest.py
- CONTRIBUTING.md
- cov.xml
- explainerdashboard.gif
- justfile
- LICENSE.txt
- MANIFEST.in
- pyproject.toml
- README.md
- RELEASE_NOTES.md
- TODO.md
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/oegedijk/explainerdashboard
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd explainerdashboard
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. Python
쉬움 추천사전 준비물
<STUDIO_URL>/jupyter/default/proxy/8051/
이 명령어를 터미널에 그대로 입력해 실행하세요.
--requests-pathname-prefix="/jupyter/default/proxy/8051/"
이 명령어를 터미널에 그대로 입력해 실행하세요.
에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.
이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.
// repository documentation
Was this content helpful?
(0 ratings)
