45 skills found · Page 1 of 2
oegedijk / ExplainerdashboardQuickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
linkedin / FastTreeSHAPFast SHAP value computation for interpreting tree-based models
archd3sai / Customer Survival Analysis And Churn PredictionIn this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.
ModelOriented / TreeshapCompute SHAP values for your tree-based models using the TreeSHAP algorithm
pablo14 / Shap ValuesShap values for model interpretation
AidanCooper / Shap ClusteringHow to use SHAP values for better cluster analysis
wilsonjr / ClusterShapleyExplaining dimensionality results using SHAP values
wilsonjr / SHAP FSelectionUsing SHAP values as feature selection mechanism
oegedijk / ExplainingtitanicA demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc
AmirhosseinHonardoust / Shap MiniA minimal, reproducible explainable-AI demo using SHAP values on tabular data. Trains RandomForest or LogisticRegression models, computes global and local feature importances, and visualizes results through summary and dependence plots, all in under 100 lines of Python.
helenaEH / SHAP TutorialTutorial on how to use the SHAP library to explain the feature importance with Shapley values.
SeanPLeary / Shapley Values H2o ExampleShapley Values with H2O AutoML Example (ML Interpretability)
haghish / ShapleyWeighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Ratheshan03 / ExplainableFLExplainableFL is a PIP Python package designed to bring explainability to Federated Learning models using SHAP values. It provides easy-to-use methods to visualize the impact of model features and privacy mechanisms on model performance.
JHang2020 / Shap MixIJCAI 2024 Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action Recognition
adiag321 / CRM Analysis For Marketing DataIn this project, we have to create a predictive model which allows the company to maximize the profit of the next marketing campaign
oschulz / ValueShapes.jlDuality of view between named variables and flat vectors in Julia
harris-chris / Joint Shapley ValuesSource code for the Joint Shapley values: a measure of joint feature importance
TorkamaniLab / ZoishZoish is a Python package that streamlines machine learning by leveraging SHAP values for feature selection and interpretability, making model development more efficient and user-friendly
tvmendoza / ShapleyValuesThis is a simple python script that calculates Shapley Values and their average.
