Topic: shapley Goto Github
Some thing interesting about shapley
Some thing interesting about shapley
shapley,Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Organization: astrazeneca
shapley,Amazon SageMaker Solution for explaining credit decisions.
Organization: awslabs
shapley,This repository contains the code for machine learning models designed to predict the outcomes of horse races, with SHAP (SHapley Additive exPlanations) interpretation incorporated for enhanced model interpretability.
User: beckypangpang
shapley,The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
User: benedekrozemberczki
shapley,Fast approximate Shapley values in R
User: bgreenwell
Home Page: https://bgreenwell.github.io/fastshap/
shapley,Multi-Touch Attribution
User: eeghor
shapley,Compute Shapley-Shorrocks value decompositions
User: elbersb
shapley,This repository contains an example of how to implement the shap library to interpret a machine learning model.
User: fernandolpz
shapley,Predicting Demand in Primary Health Care Centers in Lebanon: Insight from Syrian Refugees Crisis
User: hiyamgh
shapley,A lightweight implementation of removal-based explanations for ML models.
User: iancovert
shapley,For calculating global feature importance using Shapley values.
User: iancovert
shapley,For calculating Shapley values via linear regression.
User: iancovert
shapley,Analytical computation of rolling and expanding Shapley values for time-series data.
User: jasonjfoster
shapley,Trained a classifier by using labeled data and oversampling and undersampling techniques to predict if a borrower will default on a loan. The model is intended to be used as a reference tool to help investors make informed decisions about lending to potential borrowers based on their ability to repay. The purpose is to lower risk & maximize profit.
User: jianninapinto
shapley,Counterfactual SHAP: a framework for counterfactual feature importance
Organization: jpmorganchase
shapley,Counterfactual Shapley Additive Explanation: Experiments
Organization: jpmorganchase
shapley,In this repository you will fine explainability of machine learning models.
User: laminetourelab
shapley,Exploratory data analysis, model development and model explainability for the heart disease web application. Stack: Databricks, Pyspark, MLFlow, AutoML, Shapley, Docker.
User: leo-cb
shapley,Flask app that predicts the risk of heart disease based on a GBT ML model, and shows the confidence in the prediction as well as the factors behind the prediction (explainability).
User: leo-cb
shapley,Save thousands of API calls. Custom model & dataset aiming at predicting a game difficulty score ("lobby avg kd") without calling players' games history stats and profiles.
User: matthieuvion
Home Page: https://warzone1-kd.streamlit.app
shapley,A project for Intelligent Systems course done in 2019.3, it's a regression model using the XGBoost algorithm to predict future values โโof investment fund shares.
User: mesquita97
shapley,Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
Organization: modeloriented
Home Page: https://ModelOriented.github.io/iBreakDown/
shapley,Search vector Shapley in cooperative game
User: nekit-vp
shapley,Explaining the output of machine learning models with more accurately estimated Shapley values
Organization: norskregnesentral
Home Page: https://norskregnesentral.github.io/shapr/
shapley,An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
User: nredell
shapley,A Julia package for interpretable machine learning with stochastic Shapley values
User: nredell
Home Page: https://nredell.github.io/ShapML.jl/dev/
shapley,FastAPI for gathering LocationIQ bounding box and PurpleAir Sensor Data then creating interpolated GeoJson using KNN-Regression
Organization: oxygen-oriented-programming
shapley,This is an official repository for "2D-Shapley: A Framework for Fragmented Data Valuation" (ICML2023).
Organization: reds-lab
shapley,ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based models.
User: salimamoukou
shapley,Shapley Values with H2O AutoML Example (ML Interpretability)
User: seanpleary
shapley,A game theoretic approach to explain the output of any machine learning model.
Organization: shap
Home Page: https://shap.readthedocs.io
shapley,Jupyter Notebook Templates for quick prototyping of machine learning solutions
User: shubh1608
shapley,streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
User: snehankekre
Home Page: https://pypi.org/project/streamlit-shap/
shapley,Using data within first 24 hours of intensive care to develop a machine learning model that could improve the current patient survival probability prediction system (apache_4a) and is more generalized to patients outside of the US
User: tam-ng
shapley,Interpretable machine learning based on Shapley values
User: tsurubee
shapley,Examines fairness metrics for models including gender stereotyping versus group differences due to appropriate predictors. Also explores feature bias mitigation
User: vla6
shapley,Analysing Time series and spatiotemporal data
User: wafama
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