PulmonomicsLab/mcdr-mtb-standalone-v2

Multi-class classification of drug resistance in MTB clinical isolates

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carlacodes/boostmodels

gradient-boosted regression and decision tree models on behavioural animal data

Language: Python - Size: 1.24 GB - Last synced: 4 days ago - Pushed: 4 days ago - Stars: 3 - Forks: 0

xplainable/xplainable

Real-time explainable machine learning for business optimisation

Language: Python - Size: 16.3 MB - Last synced: 4 days ago - Pushed: 4 days ago - Stars: 52 - Forks: 5

GPUK79/data-science-portfolio

This repository contains the Python scripts that I have written and run to execute a series of analytic model developments using datasets taken from the book "The Elements of Statistical Elements" by Hastie, Tibshirani, Friedman

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MoritzM00/Linkit-Beginner-Challenge-Explainable-ML

Repository for the Linkit Beginner Challenge on Explainable ML using SHAP values.

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tvdboom/ATOM

Automated Tool for Optimized Modelling

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ModelOriented/treeshap

Compute SHAP values for your tree-based models using the TreeSHAP algorithm

Language: R - Size: 17.7 MB - Last synced: 9 days ago - Pushed: 4 months ago - Stars: 75 - Forks: 21

linkedin/FastTreeSHAP

Fast SHAP value computation for interpreting tree-based models

Language: Python - Size: 152 MB - Last synced: 9 days ago - Pushed: 11 months ago - Stars: 492 - Forks: 30

mljar/mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Language: Python - Size: 9.49 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 2,923 - Forks: 381

haghish/shapley

Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles

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shap/shap

A game theoretic approach to explain the output of any machine learning model.

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MAIF/shapash

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

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jroberts225/SHAP-LIME-for-UNSW-15

Scripts for generating SHAP & LIME explainations and their corresponding plots

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oegedijk/explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Language: Python - Size: 80.3 MB - Last synced: 19 days ago - Pushed: about 2 months ago - Stars: 2,227 - Forks: 320

predict-idlab/powershap

A power-full Shapley feature selection method.

Language: Python - Size: 4.64 MB - Last synced: 18 days ago - Pushed: 18 days ago - Stars: 179 - Forks: 17

hoomanbing/Twitter-Data-Sentiment-Analysis-using-Ensemble-Learning-and-XAI

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wyattowalsh/higher-education-simulation

Full Python implementation of an agent-based simulation model of generalized higher education institutions. Thousands of experiments are conducted and model feature significance is found through regression, SHAP, and permutation.

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Ashutosh27ind/census_income_prediction

The case study is a traditional supervised binary classification problem based on the UCI Machine Learning Repository "adult" dataset.

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izam-mohammed/shap Fork of shap/shap

SHAP (SHapley Additive exPlanations) is an open-source library for model interpretability and explainable AI. It provides a unified framework for interpreting and understanding the predictions of any machine learning model, including deep neural networks, gradient boosting machines and more.

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ModelOriented/survex

Explainable Machine Learning in Survival Analysis

Language: R - Size: 309 MB - Last synced: 19 days ago - Pushed: about 1 month ago - Stars: 88 - Forks: 10

AstraZeneca/awesome-shapley-value

Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)

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ModelOriented/kernelshap

Efficient R implementation of SHAP

Language: R - Size: 2.36 MB - Last synced: 23 days ago - Pushed: 4 months ago - Stars: 30 - Forks: 7

nredell/ShapML.jl

A Julia package for interpretable machine learning with stochastic Shapley values

Language: Julia - Size: 529 KB - Last synced: 12 days ago - Pushed: 15 days ago - Stars: 80 - Forks: 7

rdolor/research-collections

Contains a collection of my experimentations, explorations, and data analysis of random datasets

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Montimage/maip

Montimage AI Platform (MAIP) provides users with easy access to AI services developed by Montimage, through a friendly and intuitive interface.

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NaquibAlam/TheMisfits

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ing-bank/probatus

Validation (like Recursive Feature Elimination for SHAP) of (multiclass) classifiers & regressors and data used to develop them.

Language: Python - Size: 12.7 MB - Last synced: 19 days ago - Pushed: 28 days ago - Stars: 122 - Forks: 39

ModelOriented/shapviz

R package for SHAP plots

Language: R - Size: 27.7 MB - Last synced: 14 days ago - Pushed: 3 months ago - Stars: 65 - Forks: 10

TannerGilbert/Model-Interpretation

Overview of different model interpretability libraries.

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JK-Future-GitHub/NBA_Champion

I will predict the 2023 NBA Champion using Machine Learning

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JK-Future-GitHub/NBA_MVP

I will predict the 2023 NBA MVP using Machine Learning

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cerlymarco/shap-hypetune

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

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SirWilliam254/Feature-Importance

This repo is all about feature importance. Whereby we look at the ways one can identify if a feature is worth having in the model or rather if it has a significant influence in the prediction. The methods are model-agnostic.

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feedzai/timeshap

TimeSHAP explains Recurrent Neural Network predictions.

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aaronwtr/interpreting-ml-based-drops

This repository accompanies my research into the interpretability of DNA Damage Repair Outcome Predictors (DROPs). By analyzing these models using interpretability methods, we hope to uncover what features specifically are driving the accuracy of these prediction models.

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ytanaka-bio/cisMultiDeep

Workflow to identify functional cis-regulatory regions for each annotated cell type

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Vanyaeremin/yandex_practicum_data_science

В данном репозитории хранятся выполненные мною проекты, в рамках обучения на курсе Яндекс. Практикума "Специалист по Data Science"

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carlacodes/neuraldecoding

scripts used for neural decoding of single and multi unit auditory cortex data

Language: Python - Size: 3.37 MB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 2 - Forks: 1

raquelcolares/machine_learning_UFMG

My repository of Machine Learning by UFMG

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tedoaba/House-Price-Prediction-App

House-Price-Prediction-App

Language: Python - Size: 710 KB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 1 - Forks: 0

MI2DataLab/survshap

SurvSHAP(t): Time-dependent explanations of machine learning survival models

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spags093/spotify_song_data

Part 1: Analysis of Spotify song data that uses Machine Learning to determine what features make a "hit" song on Spotify.

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eXascaleInfolab/ImputeVIS

ImputeVIS - eXascale Infolab, University of Fribourg, Switzerland

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Silvano315/Stroke_Prediction

Stroke prediction with machine learning and SHAP algorithm using Kaggle dataset

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Kaushikjas10/Liquefaction-gravel-eml-2023

This repository is associated with interpretable/explainable ML model for liquefaction potential assessment of gravelly soils. This model is developed using LightGBM and SHAP.

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ckorgial/xAI-CAAE

Pytorch Implementation of the Explainable Conditional Adversarial Autoencoder using Saliency Maps and SHAP (J. of Imaging - MDPI)

Language: Python - Size: 148 KB - Last synced: about 1 month ago - Pushed: about 1 month ago - Stars: 6 - Forks: 1

fau-masters-collected-works-cgarbin/shap-experiments-image-classification

Exploring SHAP feature attribution for image classification

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yerlikayaperi/shap-for-chem Fork of schwallergroup/CuCNCC

Complementary code to a project on the potential of machine learning as a tool for chemical synthesis using SHAP.

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marvinbuss/ExplainableML-Vision

This repository introduces different Explainable AI approaches and demonstrates how they can be implemented with PyTorch and torchvision. Used approaches are Class Activation Mappings, LIMA and SHapley Additive exPlanations.

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venkat-a/Term-Deposit-Marketing-Prediction

client subsection to a term deposit

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snehankekre/streamlit-shap

streamlit-shap provides a wrapper to display SHAP plots in Streamlit.

Language: Python - Size: 4.52 MB - Last synced: 3 months ago - Pushed: almost 2 years ago - Stars: 67 - Forks: 7

ZeyTrack/digit-recognizer

identify digits from a dataset of tens of thousands of handwritten images.

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akthammomani/Menara-App-Predict-House-Price-CA

Build a Web App called Menara to Predict, Forecast House Prices and search GreatSchools in California - Bay Area

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Davide-Ettori/XAI_Research-Explainable-Neural-Networks

Research on various XAI methods: NAM, SHAP, EBM and Adversarial Attack

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hi-paris/XPER

A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.

Language: Python - Size: 6.68 MB - Last synced: 15 days ago - Pushed: 6 months ago - Stars: 10 - Forks: 1

nredell/shapFlex

An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model

Language: R - Size: 2.13 MB - Last synced: about 1 month ago - Pushed: almost 4 years ago - Stars: 70 - Forks: 7

Abdul-AA/Kickstarters

Predictive Modeling and Clustering Insights for Kickstarter Success

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LennardZuendorf/thesis-files

Collection of associated files for my bachelor thesis

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LennardZuendorf/thesis-webapp

Webapp/Application implemention of my thesis about XAI and Interpretability of Transformer Models.

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back1ply/Key-Influencers

Replicate Power BI Key Influencer visual in python

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Abdul-AA/Causal-Inference-Life-Expectancy

Using CausalML to assess the causal impact of a country's development status on its life expectancy

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OmidGhadami95/EfficientNetV2_CatVSDog

Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.

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IvanSaravanja2306/Credit_Card_Approval_Prediction

Credit Card Approval Prediction based on users' historic data.

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AidanCooper/shap-analysis-guide

How to Interpret SHAP Analyses: A Non-Technical Guide

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knaaga/death-risk-prediction-models

Tree based models to predict 10 yr risk of death using the NHANES epidemiology dataset

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rhenkin/rforceplots

Wrapper for shapjs node package for easy force plots in R without Python dependencies

Language: R - Size: 248 KB - Last synced: 4 months ago - Pushed: about 2 years ago - Stars: 1 - Forks: 0

REAtes/Directing-App-Customers-to-Subscription

The primary goal of this project is to convert free users of a financial tracking app into paid members. This conversion will be achieved by building a model that identifies users who are unlikely to enroll in the paid version of the app.

Language: Python - Size: 1.84 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0

vigneashpandiyan/Additive-Manufacturing-Sensor-Selection-Acoustic-Emission

Sensor selection for process monitoring based on deciphering acoustic emissions from different dynamics of the Laser Powder Bed Fusion process using Empirical Mode Decompositions and Interpretable Machine Learning

Language: Python - Size: 155 KB - Last synced: 4 months ago - Pushed: 8 months ago - Stars: 1 - Forks: 1

henningheyen/ResponsibleAI-Project

This project aims to touch on the most important topics in the field of Responsible AI including bias, fairness, interpretability, error analysis and counterfactuals. Why apply those concepts to the adult dataset

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erik1110/Data-Science

iThome 13th-ironman (2021) - Data Science Learning Roadmap about Python

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annabelleluo/HELOC

This is the HKU STAT3612 project, 2020. This is an interpretable machine learning project for credit scoring with Home Equity Line of Credit data.

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ayseirmak/ModelExplainability_TurkishSentimentAnalysis

An explainability model that can be applied to BERT-based Turkish sentiment analysis models has been developed and its performance has been compared with model spesific Layer-wise relevance propogation expailanbility model of Hila Chefer.

Language: Python - Size: 2.06 MB - Last synced: 4 months ago - Pushed: 6 months ago - Stars: 0 - Forks: 0

beckypangpang/horse-racing-prediction-SHAP

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.

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w3raza/shapProjekt Fork of Saffons/shapProjekt

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etetteh/e

Language: Python - Size: 51.1 MB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 0 - Forks: 0

cloudera/CML_AMP_Explainability_LIME_SHAP

Learn how to explain ML models using LIME and SHAP.

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Vicarious987/cub-orders-number-forecasting

Прогнозирование числа заказов такси на основе временных рядов.

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Vicarious987/car_price_prediction

Предсказание стоимости автомобилей.

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Vicarious987/hotel_false_booking_detection

Предсказание отмены брони номера в отеле.

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rishuatgithub/explainable-ai-app

Streamlit app repository for Explainable AI application

Language: Python - Size: 58.6 KB - Last synced: about 1 month ago - Pushed: 9 months ago - Stars: 2 - Forks: 0

mingo514/PCA_explainability_Paper---MATH60629A_MACHINE_LEARNING_I

This project aims to enhance the interpretability of Principal Component Analysis (PCA) by integrating explainability tools and advanced dimensionality reduction techniques such as UMAP or t-SNE.

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josesousaribeiro/XAI-Benchmark

This is a repository for reproducibility purposes. In this research, a large number of datasets were used to create different ML models, which were then explained by XAI measures. Seeking to identify situations where XAI measures agreed or disagreed with each other.

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josesousaribeiro/eXirt-XAI-Pipeline

This is a repository for reproducibility purposes. In this research, a large number of datasets were used to create different ML models, which were then explained by XAI measures. Proposing a new measure of XAI called eXirt.

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McGill-MMA-EnterpriseAnalytics/datasectuals

Predicting whether or not a person deposits money after a marketing campaign. Gain insights to develop the best strategy in the next marketing campaign

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madhava20217/Local-to-Global-Explanations

Get global perspectives from local explanations.

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AjNavneet/CreditRiskPrediction_LightGBM_Hyperopt_SHAP

Predictive model for loan defaulters using LightGBM, HyperOpt and SHAP model interpretation.

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AjNavneet/CreditDelinquencyAnalysis_Regression_LIME_SHAP

Credit delinquency analysis on borrower information and historical records using classical and advanced regression techniques along with LIME,SHAP.

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qisuqi/Attn_ED

Using Encoder-Decoder with attention mechanism as the predictive model, and choosing from DiCE, LIME, and SHAP to explain the model

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sonnguyen129/Accident-Severity-Prediction

Predicting the severity of accident

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MoshiurRahmanFaisal/Predictive-Analysis-with-Explainable-AI

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anondo1969/SHAMSUL

SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction

Language: Python - Size: 2.53 MB - Last synced: 6 months ago - Pushed: 6 months ago - Stars: 1 - Forks: 0

tommartensen/tic

TIC is a library that acts as a Toolbox for Interpretability Comparison.

Language: Python - Size: 212 KB - Last synced: about 1 month ago - Pushed: over 1 year ago - Stars: 2 - Forks: 0

StarrySkyrs/Spotify_Popularity_Prediction

Built an ensemble model on the Spotify dataset to determine the popularity of songs and study feature importance using SHAP.

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lizruonan/limeproject

Comparison between LIME and SHAP

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runstats21/college-score-card-analysis

Language: Jupyter Notebook - Size: 39.6 MB - Last synced: 2 months ago - Pushed: 2 months ago - Stars: 0 - Forks: 0

LamineTourelab/Explainable-AI

In this repository you will fine explainability of machine learning models.

Size: 8.79 KB - Last synced: 5 months ago - Pushed: over 1 year ago - Stars: 3 - Forks: 0

wellylin8916/Stock-Crash-Risk-on-XGBoost-Model

xgboost預測股價崩盤風險

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john-fante/flower-detection-meta-learning

Flower Detection w/Meta Learning(ViT, CatBoost, SHAP)

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john-fante/malware-classification

Malware Classification w/CatBoost and SHAP

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khames-lab/Used-Automobile-Price-Prediction

📌Used Automobile Price Prediction

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