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A game theoretic approach to explain the output of any machine learning model.
Created
2016-11-22
2,794 commits to master branch, last one 4 days ago
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Created
2018-11-05
1,227 commits to master branch, last one 19 days ago
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Created
2020-04-29
1,707 commits to master branch, last one 23 days ago
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
Created
2019-10-30
1,376 commits to master branch, last one about a month ago
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
Created
2021-05-16
30 commits to main branch, last one 11 months ago
Fast SHAP value computation for interpreting tree-based models
Created
2022-01-24
40 commits to master branch, last one about a year ago
Shapley Interactions and Shapley Values for Machine Learning
Created
2023-10-17
818 commits to main branch, last one 17 days ago
利用lightgbm做(learning to rank)排序学习,包括数据处理、模型训练、模型决策可视化、模型可解释性以及预测等。Use LightGBM to learn ranking, including data processing, model training, model decision visualization, model interpretability and pre...
Created
2019-11-10
20 commits to master branch, last one 2 years ago
A power-full Shapley feature selection method.
Created
2022-03-16
176 commits to main branch, last one 9 months ago
TimeSHAP explains Recurrent Neural Network predictions.
Created
2022-01-10
53 commits to main branch, last one about a year ago
Automated Tool for Optimized Modelling
Created
2019-07-03
1,008 commits to master branch, last one 7 months ago
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Created
2022-04-29
87 commits to master branch, last one 2 years ago
Validation (like Recursive Feature Elimination for SHAP) of (multiclass) classifiers & regressors and data used to develop them.
Created
2020-11-09
1,194 commits to main branch, last one 5 months ago
Explainable Machine Learning in Survival Analysis
r
xai
shap
cox-model
r-package
brier-scores
biostatistics
censored-data
time-to-event
cox-regression
explainable-ai
explainable-ml
interpretable-ml
machine-learning
survival-analysis
variable-importance
explanatory-model-analysis
explainable-machine-learning
interpretable-machine-learning
probabilistic-machine-learning
Created
2022-08-31
480 commits to main branch, last one 7 months ago
A Julia package for interpretable machine learning with stochastic Shapley values
Created
2020-01-23
118 commits to master branch, last one 2 years ago
SHAP Plots in R
Created
2020-10-10
448 commits to main branch, last one 14 days ago
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
Created
2022-01-31
21 commits to main branch, last one 2 years ago
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Created
2022-08-03
92 commits to main branch, last one about a year ago
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Created
2020-07-30
232 commits to master branch, last one about a year ago
Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
Created
2019-11-09
94 commits to master branch, last one 4 years ago
Real-time explainable machine learning for business optimisation
Created
2022-09-22
513 commits to main branch, last one 4 months ago
How to use SHAP values for better cluster analysis
Created
2022-05-05
12 commits to main branch, last one 2 years ago
How to Interpret SHAP Analyses: A Non-Technical Guide
Created
2021-09-24
9 commits to main branch, last one 3 years ago
Overview of different model interpretability libraries.
Created
2019-12-15
17 commits to master branch, last one 2 years ago
Different SHAP algorithms
Created
2022-08-05
380 commits to main branch, last one 4 months ago
Local explanations with uncertainty 💐!
Created
2021-10-19
7 commits to main branch, last one 2 years ago
A Colab notebook for land cover mapping and monitoring using Earth Engine
Created
2023-07-28
14 commits to main branch, last one about a year ago
Developed a churn prediction model using XGBoost, with comprehensive data preprocessing and hyperparameter tuning. Applied SHAP for feature importance analysis, leading to actionable business insights...
Created
2024-08-12
16 commits to main branch, last one 5 months ago