Multi-Class Prediction of Obesity Risk ML App
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Updated
Feb 25, 2024 - Jupyter Notebook
Multi-Class Prediction of Obesity Risk ML App
An implemetation for computing the Shapley value (in polynomial time) of matching games over bounded treewidth graphs.
Frontend for ShapEmotionsCorrectionAPI
Dilated Convolutional Autoencoder for univariate Time Series
Shapley and Banzhaf vectors of a formal concept
Codes for reproducing the results of arXiv:2207.04157
Feature engineering, selection and XGBoost modeling for the Kaggle House Prices Regression competition.
Application on Markov Chain and Removal Effect (Attribution Modeling)
An academic research paper detailing an automatic method to generate customized explanations for the Shapley value.
Official implementation of our ICML'22 paper: "On the Convergence of the Shapley Value in Parametric Bayesian Learning Games".
Set of Jupyter notebooks and geospatial data developed by the MAPSPADES project to study desertification in the Algerian steppe using EO data.
This repository consists the supplemental materials of the paper "Decomposition of Expected Goal Models: Aggregated SHAP Values for Analyzing Scoring Potential of Player/Team".
AI applications can be found in various real-world systems, including vehicle system design and real-time car accident prediction. There is an increasing need to better explain AI-driven processes, especially in terms of potential legal disputes that might result from AI decisions. This analysis addresses this explainability and legal issues.
HERALD: An Annotation Efficient Method to Train User Engagement Predictors in Dialogs (ACL 2021)
LINe: Out-of-Distribution Detection by Leveraging Important Neurons (CVPR 2023)
Set of algorithms from System theory and analysis course
use XGBoost and Adaboost to predict heart disease and use SHAP to explain the potential factors behind the result.
2022 K-인공지능 제조 데이터 분석 경진대회(장려상)
Search vector Shapley in cooperative game
A python script to classify Titanic dataset (Survived and not Survived) by applying different Machine Learning Algorithms have been used such as Logistic Regression, SVM, KNN, Decision Tree and Random Forest.
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