GitHub topics: shap
Taylanozveren/Ai_Project_Chatbot_Fintech
End-to-end crypto analytics & Ai Project ⇢ data pipeline, ML & LSTM signals, Streamlit dashboard. Research only—no financial advice.
Language: Jupyter Notebook - Size: 72.1 MB - Last synced at: about 12 hours ago - Pushed at: about 12 hours ago - Stars: 1 - Forks: 0
sp-muramutsa/agriculture
This project analyzes the importance of soil features in AI/ML-based prediction of the optimal crop for given soil measurements using SHAP(SHapley Additive exPlanations) .
Language: Jupyter Notebook - Size: 543 KB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 0 - Forks: 0
Demetreous/Spotify-Track-Recommender-System-and-Popularity-Regression
ML project leveraging Spotify audio data for track popularity prediction and music recommendation using XGBoost, KNN, and SHAP
Language: Jupyter Notebook - Size: 1.99 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 0 - Forks: 0
muhammadmutahir/CreditRiskModel_CRA_using_XGBoost_Neural_Network_Random_Forest_Regression_Sourav_Basu
This repository contains a credit risk analytics project that uses logistic regression, decision trees, and various data analysis techniques. Explore the code and resources in Jupyter Notebook format to understand the model's performance and insights. 🐱💻📊
Language: Jupyter Notebook - Size: 522 KB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 0 - Forks: 0
ModelOriented/shapviz
SHAP Plots in R
Language: R - Size: 42.3 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 98 - Forks: 15
ShrutikSai/Predicting-Customer-Churn-for-a-Telecom-Company
An end-to-end real-world ML project to predict customer churn using EDA, Feature Engineering, XGBoost, SHAP, and Business Insights. Includes data aggregation, ETL, NLP, and model deployment-ready outputs.
Language: Jupyter Notebook - Size: 1.01 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0
Cuonghoangit/GeoMineralInsight
This project uses machine learning to analyze geological, geochemical, aeromagnetic, and remote sensing data over 39,000 sq. km in southern India. It identifies high-probability zones for concealed Au, Cu, and PGE deposits using XGBoost, SHAP, and GeoPandas. Key features include automated pipelines, explainable AI, and GIS-ready maps.
Language: Jupyter Notebook - Size: 7.38 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 0
HangOn6/CreditRiskModel_CRA_using_XGBoost_Neural_Network_Random_Forest_Regression_Sourav_Basu
Improving credit risk model using Machine learning techniques. We use a host of ml models and neural network to solve the issue.
Language: Jupyter Notebook - Size: 533 KB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 0 - Forks: 0
shap/shap
A game theoretic approach to explain the output of any machine learning model.
Language: Jupyter Notebook - Size: 280 MB - Last synced at: 5 days ago - Pushed at: 8 days ago - Stars: 24,020 - Forks: 3,379
xplainable/xplainable
Real-time explainable machine learning for business optimisation
Language: Python - Size: 20.8 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 61 - Forks: 6
trinhbao1505/Is-Deleting-the-Dataset-of-a-Self-Aware-AGI-ethical-Does-It-Possess-a-Soul-by-Self-Awareness-
Is Deleting the Dataset of a Self-Aware AGI ethical? Does It Possess a Soul by Self-Awareness? Assessing the Existence of a Soul and Ethical Implications Using Fuzzy Logic
Size: 1.95 KB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 1 - Forks: 0
tim-toothed/multilingual-sentiment-SHAP
Explaining SHAP visual explanations for Multilingual Sentiment Analysis
Language: Jupyter Notebook - Size: 715 KB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 0 - Forks: 0
mmschlk/shapiq
Shapley Interactions and Shapley Values for Machine Learning
Language: Python - Size: 312 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 560 - Forks: 36
Algi21/Supervised-Learning-Classification
Project Supervised Learning - Classification untuk memprediksi customer churn atau tidak berdasarkan dataset suatu perusahaan telekomunikasi.
Language: Jupyter Notebook - Size: 647 KB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 0 - Forks: 0
violettance/bestseller_anatomy
The platform showcases narrative analysis outputs from 2024’s bestselling fiction and allows users to upload their own manuscripts for comparison, with a bestseller prediction module coming soon
Language: TypeScript - Size: 2.25 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 0 - Forks: 0
Rahul-2006/Heart-Attack-Risk-Prediction
This is a research project based on Heart Attack Risk Prediction Using Machine Learning and SHAP Explainability
Language: Jupyter Notebook - Size: 1.42 MB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 0 - Forks: 0
miltiadiss/CEID_NE577-5G-Architectures-Technologies-Applications-and-Key-Performance-Indexes
This project involves predicting the downlink bitrate of mobile devices in 5G networks using machine learning (XGBoost Regressor) and deep learning (LSTM model). It includes data preprocessing, training and evaluation of the models, applying explainable AI (XAI) techniques such as SHAP, and optimizing feature selection based on XAI insights.
Language: Jupyter Notebook - Size: 64.9 MB - Last synced at: 6 days ago - Pushed at: 15 days ago - Stars: 3 - Forks: 0
Jiayi-Njucm/early-stage-ckd-prediction
[eClinicalMedicine] Identification and validation of an explainable early-stage chronic kidney disease prediction model: a multicenter retrospective study
Language: Jupyter Notebook - Size: 377 KB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 0 - Forks: 0
NilaBlueshirt/Classification_LKdata
A binary classification workflow for microbiome data, explaining models with SHAP to find the most important microbiome features.
Language: Jupyter Notebook - Size: 331 KB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 0 - Forks: 0
DanteTrb/fall-risk-predictor
From ICOT(Latina) to Fall Risk Prediction
Language: Python - Size: 177 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 0 - Forks: 0
MAIF/shapash
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
Language: Jupyter Notebook - Size: 61.6 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 2,893 - Forks: 348
Abdiasarsene/RouterWise-Server-Predictive-Analytics-for-Shipments
RouterWise is a production-grade, modular MLOps pipeline built to optimize supply chains in the sensitive and prestigious art logistics sector. It is the intelligent backend of the upcoming PrecisioArt platform (Django-based), and delivers predictive insights and smart routing through a fully automated, monitored, and versioned ML lifecycle.
Language: Jupyter Notebook - Size: 7.89 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 0 - Forks: 0
santiagoahl/risk-model-for-credit-loans
Risk prediction model to estimate credit provision
Language: Jupyter Notebook - Size: 12.9 MB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0
kahramankostas/IoTGeM
IoT Attack Detection with machine learning
Language: Jupyter Notebook - Size: 79.1 MB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 27 - Forks: 6
sarthakm402/Loan_Predictor
Building loan_predictor with explainability
Language: Python - Size: 83 KB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0
Borun3193/California_Housing_Price_Prediction_XGBoost
Machine Learning Regression Model with FastAPI
Language: Jupyter Notebook - Size: 850 KB - Last synced at: 1 day ago - Pushed at: 13 days ago - Stars: 0 - Forks: 0
afairless/binary_classification_shap
Run histogram-based gradient boosted trees binary classifier on generated data and interpret results with standard metrics, SHAP, and supervised clustering
Language: Python - Size: 22.5 KB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0
tuni56/churn-prediction-streamlit
Language: Python - Size: 0 Bytes - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 0 - Forks: 0
NeilQue/dsci_thesis
Predictive Modeling of Marikina River Water Level using Artificial Neural Networks
Language: Jupyter Notebook - Size: 74.9 MB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0
Jainab-khanam/loan-prediction-shap
Predict loan approvals using machine learning with SHAP explainability. Analyze customer data, build interpretable models, and visualize feature impact for business decision support.
Language: Jupyter Notebook - Size: 482 KB - Last synced at: 21 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0
SKT1803/ai-explanation-tool-grid-explainer
Visual AI explanation tool using grid-based occlusion for CNN interpretability.
Language: Jupyter Notebook - Size: 5.31 MB - Last synced at: 22 days ago - Pushed at: 23 days ago - Stars: 0 - Forks: 0
japgarrido/Hackathon-The-Summer-Song-Oracle
Este proyecto, desarrollado para la Hackathon de Oracle 2025, busca predecir la popularidad de canciones para identificar la próxima canción del verano.
Language: Jupyter Notebook - Size: 46.5 MB - Last synced at: 17 days ago - Pushed at: 23 days ago - Stars: 2 - Forks: 0
Chetnas8/acaml-web-app
ACAML is an Adaptive Constraint-Aware AutoML web app built with Streamlit. It automatically selects the best model for regression or classification tasks using FLAML, displays performance metrics, and provides SHAP-based feature explanations. Empower users to run and interpret ML models easily.
Language: Python - Size: 443 KB - Last synced at: 23 days ago - Pushed at: 23 days ago - Stars: 0 - Forks: 0
abdesemt/GBoost
A tool for Boosting Discord Servers
Size: 8.79 KB - Last synced at: 24 days ago - Pushed at: 24 days ago - Stars: 0 - Forks: 0
dkavargy/KANVAS
A skill-based job classification framework using Kolmogorov–Arnold Networks (KANs)
Language: Python - Size: 164 KB - Last synced at: 25 days ago - Pushed at: 25 days ago - Stars: 4 - Forks: 1
aimaster-dev/default_loan_prediction
This project automates bank credit risk assessment using AI and machine learning models to predict loan defaults. It streamlines the credit process with predictive analytics, model evaluation, explainability (SHAP), and deployment readiness.
Language: JavaScript - Size: 2.82 MB - Last synced at: 15 days ago - Pushed at: 25 days ago - Stars: 9 - Forks: 1
divinesaun/claxon_loan_default
A machine learning project focused on predicting the Probability of Default (PD) on loans using historical financial and demographic data. The project includes data preprocessing, feature engineering, model training, hyperparameter tuning, and interpretability using SHAP values.
Language: Jupyter Notebook - Size: 1.26 MB - Last synced at: 26 days ago - Pushed at: 26 days ago - Stars: 0 - Forks: 0
oegedijk/explainerdashboard
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
Language: Python - Size: 82.3 MB - Last synced at: 26 days ago - Pushed at: about 2 months ago - Stars: 2,399 - Forks: 340
predict-idlab/powershap
A power-full Shapley feature selection method.
Language: Python - Size: 4.64 MB - Last synced at: 14 days ago - Pushed at: about 1 year ago - Stars: 208 - Forks: 22
Preetam2303/tcga-biomarker-pipeline
R pipeline for TCGA transcriptomics biomarker discovery with ML & SHAP
Language: R - Size: 41 KB - Last synced at: 18 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
SagharShafaati/Explainable-Air-Quality-Management
This repository provides the Python code for "Explainable Air Quality Management", featuring federated learning with adaptive aggregation, SHAP-based interpretability, and anomaly detection using PrefixSpan. It enhances AQI prediction accuracy and transparency across IoT sensor networks.
Size: 13.7 KB - Last synced at: 30 days ago - Pushed at: 30 days ago - Stars: 0 - Forks: 0
AbhaySingh71/AI-Powered-Healthcare-Intelligence-System
The AI-Powered Healthcare Intelligence Network is an AI-driven system offering disease prediction, drug recommendations, heart disease risk assessment, and an AI medical chatbot. Using ML, NLP, and LLMs, it provides accurate diagnoses, insights, and recommendations, enhancing healthcare accessibility, efficiency, and decision-making .
Language: Jupyter Notebook - Size: 63.5 MB - Last synced at: 22 days ago - Pushed at: 4 months ago - Stars: 5 - Forks: 2
DanteTrb/Buffett_Evaluator
ML + SHAP + Streamlit: A Buffett-style stock evaluator built for explainable financial decisions.
Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
Language: Python - Size: 152 MB - Last synced at: 26 days ago - Pushed at: almost 2 years ago - Stars: 540 - Forks: 34
ModelOriented/survex
Explainable Machine Learning in Survival Analysis
Language: R - Size: 309 MB - Last synced at: 26 days ago - Pushed at: about 1 year ago - Stars: 112 - Forks: 10
tameTNT/evaluating-xai-remote-sensing
My final year (level 3) self-proposed dissertation project undertaken at Durham University in 2024/25 covering satellite imagery, deep learning, explainable AI (xAI), and evaluation metrics for xAI. Submitted to ECAI2025.
Language: Jupyter Notebook - Size: 170 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
ModelOriented/treeshap
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Language: R - Size: 19.7 MB - Last synced at: 20 days ago - Pushed at: 11 months ago - Stars: 88 - Forks: 24
ShadyDream222/forecasting_intraday_prices_GB_power_market
A data-driven project forecasting intraday electricity prices in the GB power market using SARIMAX and XGBoost. Combines market data, demand/generation forecasts, and model explainability tools like SHAP.
Language: Jupyter Notebook - Size: 1.18 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
miolab/jupyterlab_poetry
JupyterLab runtime environment with Poetry and Docker management.
Language: Jupyter Notebook - Size: 107 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 7 - Forks: 0
feedzai/timeshap
TimeSHAP explains Recurrent Neural Network predictions.
Language: Jupyter Notebook - Size: 1.53 MB - Last synced at: 29 days ago - Pushed at: over 1 year ago - Stars: 175 - Forks: 32
faizaliyaqat/Speech-emotion-recognition
Speech Emotion Recognition using Wav2Vec 2.0 + Random Forest Real-time emotion detection system built with Streamlit, trained on RAVDESS and SAVEE datasets using Wav2Vec 2.0 features and a Random Forest classifier. Includes SHAP explainability and audio waveform visualization.
Language: Python - Size: 17.6 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
cloudera/CML_AMP_Explainability_LIME_SHAP
Learn how to explain ML models using LIME and SHAP.
Language: Jupyter Notebook - Size: 4.65 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 24 - Forks: 11
mananjain0220/ParkinsonClassifier-WearableML
🧠 Binary classification of Parkinson’s Disease using wearable sensor data and clinical symptoms. Built with Python, SHAP, and tree-based models on the PADS dataset.
Language: Jupyter Notebook - Size: 8.37 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
MI2DataLab/survshap
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Language: Jupyter Notebook - Size: 8.99 MB - Last synced at: 27 days ago - Pushed at: over 1 year ago - Stars: 87 - Forks: 16
ing-bank/probatus
SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.
Language: Python - Size: 17.5 MB - Last synced at: about 1 month ago - Pushed at: 2 months ago - Stars: 144 - Forks: 41
jpmorganchase/cf-shap
Counterfactual SHAP: a framework for counterfactual feature importance
Language: HTML - Size: 823 KB - Last synced at: 11 days ago - Pushed at: almost 2 years ago - Stars: 20 - Forks: 9
zuzann18/credit-risk-classification
End-to-end machine learning project for predicting loan defaults on the HMEQ home equity loan dataset. Includes data preprocessing, EDA, feature engineering, model training (Logistic Regression, Random Forest, XGBoost), hyperparameter tuning, model comparison, SHAP-based interpretability, and business recommendations
Language: HTML - Size: 2.76 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
jasjeev013/GeoMineralInsight
This project uses machine learning to analyze geological, geochemical, aeromagnetic, and remote sensing data over 39,000 sq. km in southern India. It identifies high-probability zones for concealed Au, Cu, and PGE deposits using XGBoost, SHAP, and GeoPandas. Key features include automated pipelines, explainable AI, and GIS-ready maps.
Language: Jupyter Notebook - Size: 7.38 MB - Last synced at: 20 days ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
tvdboom/ATOM
Automated Tool for Optimized Modelling
Language: HTML - Size: 826 MB - Last synced at: 21 days ago - Pushed at: 11 months ago - Stars: 159 - Forks: 14
neZorinEgor/AdsAnalyzer
📰 Platform for analyzing the effectiveness of advertising campaigns by ml and data analys
Language: Jupyter Notebook - Size: 15.3 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 6 - Forks: 0
Nadaaaaaaaaaaaaaaaaaa/agriculture-risques-analysis
Data analysis project predicting occupational risks for female agricultural workers using machine learning (XGBoost/SHAP). Includes data cleaning, EDA and predictive modeling.
Size: 0 Bytes - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
shiva8395/ml_trading_signal
AI-powered trading signal engine with FastAPI backend, Streamlit dashboard, and SHAP explainability.
Language: Python - Size: 0 Bytes - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
patricksferraz/pcr-analysis
Machine learning-powered PCR data analysis toolkit featuring transfer learning, time series forecasting, and SHAP-based model interpretability. Built with TensorFlow and scikit-learn for advanced biological data processing.
Language: Jupyter Notebook - Size: 9.66 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
ChandanaThummala/Explainable-AI-for-Breast-Cancer-Prediction
Breast Cancer Classification with Explainable AI (SHAP, LIME, PDP)
Language: Jupyter Notebook - Size: 2.86 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
patricksferraz/master-covid
A comprehensive health data analysis project using PySpark and TensorFlow for medical diagnosis and outcome prediction. Features large-scale data processing and interactive notebooks.
Language: Jupyter Notebook - Size: 12.7 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
liuktc/ML4CV_XAI
Exams project for Master in AI at UNIBO
Language: Jupyter Notebook - Size: 101 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
Shakthirekak11/Political-Speech-Manipulation-Detection
🗳️ Political Speech Manipulation Detection uncovers misinformation, bias, and hostile rhetoric in political content using advanced language models and analytical pipelines. It processes speeches, tweets, and news articles to classify truthfulness, detect sentiment, and extract rhetorical and thematic patterns.
Language: Jupyter Notebook - Size: 3.09 MB - Last synced at: 15 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
Smit-Parekh/deep-demand-forecast-retail
End-to-end Deep Learning (TFT) demand forecasting system for Retail/FMCG with automated MLOps pipeline on Google Cloud (Vertex AI) for inventory optimization. Demonstrates advanced time series modeling, feature engineering, explainability (SHAP), and scalable deployment.
Size: 3.91 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
pyladiesams/ai-in-finance-python-lecture-beginner-may2022
AI in Finance - Python interactive lecture for students studying Finance
Language: Jupyter Notebook - Size: 1.88 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 4 - Forks: 3
YouhuiPang/FX-Risk-Forecasting-System
An intuitive end-to-end web-app system that forecasts FX risk over the next 3 days, powered by explainable AI and real market data.
Language: Python - Size: 3.93 MB - Last synced at: 20 days ago - Pushed at: about 2 months ago - Stars: 2 - Forks: 0
nb71325/XAI-Stock-market-prediction
We tested 3 distinct Deep Learning models (the LSTM-GRU hybrid model turned out to be the best) to forecast AAPL price movements, focusing on the prior 90 days. We additionally incorporated RSI and MACD to better mimic the actual price. To provide more insights, we combined SHAP with GPT-2, to find out the proper time to invest in these stocks.
Language: Jupyter Notebook - Size: 59.8 MB - Last synced at: about 2 months ago - Pushed at: about 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 at: 21 days ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 0
suryadipbera1256/Epileptic-Seizure-Recognition
Machine learning techniques are increasingly applied in the classification of drugs based on biomarkers related to epileptic seizures. Various studies highlight the use of deep learning and other machine learning models to enhance seizure detection and classification from EEG data.
Language: Jupyter Notebook - Size: 431 KB - Last synced at: 8 days ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0
Rashed-alothman/student_performance_project
A machine learning-based educational technology system that predicts student academic outcomes through three specialized models: final exam mark prediction, dropout risk assessment, and pass/fail forecasting. Built with Python, Flask, and scikit-learn to help educational institutions identify at-risk students and implement timely interventions.
Language: Python - Size: 197 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
Selasie5/explainable-backend
A Fast API Backend Engine for explainable- Turn raw datasets and machine learning models into human-understandable visual stories
Language: Python - Size: 31.3 KB - Last synced at: 7 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
PERSIMUNE/explainer
ExplaineR is an R package built for enhanced interpretation of classification and regression models based on SHAP method and interactive visualizations with unique functionalities so please feel free to check it out, See ExplaineR paper at doi:10.1093/bioadv/vbae049
Language: R - Size: 17.8 MB - Last synced at: about 1 month ago - Pushed at: 9 months ago - Stars: 17 - Forks: 1
sivkri/survival-analysis-end-to-end
A comprehensive end-to-end survival analysis project using classical and deep learning models with clinical data, including preprocessing, modeling, evaluation, and interpretability.
Language: Jupyter Notebook - Size: 1.1 MB - Last synced at: 1 day ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
MechaCyberX/SCADA-AI-DETECTION
AI-powered anomaly detection system for SCADA networks using LSTM and explainable AI.
Language: Python - Size: 18.5 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
saky-semicolon/HER2-IHC-Breast-Cancer-Classification
Multi-class HER2 IHC breast cancer classification using CNN and DenseNet121 with SHAP and Grad-CAM for model interpretability
Language: Jupyter Notebook - Size: 8.99 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
anondo1969/SHAMSUL
Repository for the journal article 'SHAMSUL: Systematic Holistic Analysis to investigate Medical Significance Utilizing Local interpretability methods in deep learning for chest radiography pathology prediction'
Language: Python - Size: 32 MB - Last synced at: 11 days ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
turgunbaevaa/machineLearningProject
A complete ML project that explores feature engineering, model training (Decision Tree, Random Forest, Gradient Boosting), and model interpretation using SHAP and LIME.
Language: Jupyter Notebook - Size: 4.54 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
nredell/ShapML.jl
A Julia package for interpretable machine learning with stochastic Shapley values
Language: Julia - Size: 529 KB - Last synced at: 4 days ago - Pushed at: about 1 year ago - Stars: 90 - Forks: 8
AstraZeneca/awesome-shapley-value
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Size: 622 KB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 150 - Forks: 12
pavankethavath/Microsoft-Classifying-Cybersecurity-Incidents-with-ML
A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn
Language: Jupyter Notebook - Size: 4.54 MB - Last synced at: 16 days ago - Pushed at: 7 months ago - Stars: 4 - Forks: 0
cemdurakk/telco-customer-churn-prediction
An end-to-end machine learning project to predict customer churn in the telecom industry using XGBoost and SHAP explainability.
Language: Jupyter Notebook - Size: 484 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
Sasi-008/Credit-Risk-Prediction
Financial institutions face significant challenges in assessing the creditworthiness of loan applicants. This developed machine learning model predict the credit risk of loan applicants. The model classifies applicants into two categories: good credit risk and bad credit risk.
Language: Jupyter Notebook - Size: 1.34 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
ModelOriented/kernelshap
Different SHAP algorithms
Language: R - Size: 2.5 MB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 47 - Forks: 7
cerlymarco/shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
Language: Jupyter Notebook - Size: 122 KB - Last synced at: about 2 months ago - Pushed at: about 1 year ago - Stars: 576 - Forks: 73
AidanCooper/shap-analysis-guide
How to Interpret SHAP Analyses: A Non-Technical Guide
Language: Jupyter Notebook - Size: 7.32 MB - Last synced at: about 2 months ago - Pushed at: over 3 years ago - Stars: 53 - Forks: 8
mvharsh/Credit-Card-Offer-Acceptance-Prediction
An ethically-aware deep learning project to predict credit card offer acceptance while mitigating income-based bias using SHAP, Fairlearn, and AIF360.
Language: Jupyter Notebook - Size: 1.87 MB - Last synced at: 9 days ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0
dylan-slack/Modeling-Uncertainty-Local-Explainability
Local explanations with uncertainty 💐!
Language: Python - Size: 7.57 MB - Last synced at: about 1 month ago - Pushed at: almost 2 years ago - Stars: 40 - Forks: 15
jiangnanboy/learning_to_rank
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 prediction, etc.
Language: Python - Size: 2 MB - Last synced at: about 1 month ago - Pushed at: almost 3 years ago - Stars: 266 - Forks: 71
brickmanlab/scanvi-explainer
scANVI Explainer
Language: Python - Size: 2.64 MB - Last synced at: 23 days ago - Pushed at: 9 months ago - Stars: 3 - Forks: 0
Pramit726/Smartphone-Feature-Impact-Analysis-Score-Prediction
This project predicts smartphone scores based on key specs using machine learning, featuring model tuning (Optuna), interpretability (SHAP), and real-time inference (FastAPI).
Language: Jupyter Notebook - Size: 18.7 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0
lightxLK/SMBDuNLP
Making a project for detecting bots and fraud in social media using Deep Learning & NLP.
Language: Jupyter Notebook - Size: 368 KB - Last synced at: about 1 month ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0
11NOel11/chaos_nonchaos_predictor_nn
AI-powered chaos detection using Simple Harmonic Motion (SHM) & Double Pendulum examples! Compare a Neural Network (NN) with the Lyapunov exponent method to classify chaotic vs. non-chaotic systems. Features Deep Learning, SHAP explainability, F1-score, precision, recall, and stunning visualizations!
Language: Python - Size: 521 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0
RideneFiras/QosMLOPS
Language: HTML - Size: 21.5 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
hbaniecki/compress-then-explain
Efficient and accurate explanation estimation with distribution compression (ICLR 2025 Spotlight)
Language: Python - Size: 1.25 MB - Last synced at: 2 months ago - Pushed at: 4 months ago - Stars: 7 - Forks: 1
franciellevargas/SELFAR
The SEntence-Level FActual Reasoning (SELFAR) is a new method to improve explainable fact-checking. It relies on fact extraction and verification by predicting the news source reliability and factuality (veracity) of news articles or claims at the sentence level, generating post-hoc explanations using SHAP/LIME and zero-shot prompts.
Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0
snehankekre/streamlit-shap
streamlit-shap provides a wrapper to display SHAP plots in Streamlit.
Language: Python - Size: 4.52 MB - Last synced at: 8 days ago - Pushed at: almost 3 years ago - Stars: 86 - Forks: 9
