Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP | Scientific Reports
XGBoost: An Optimal Machine Learning Model with Just Structural Features to Discover MOF Adsorbents of Xe/Kr | ACS Omega
arXiv:2103.00949v1 [q-fin.RM] 1 Mar 2021
dalex-xgboost
SHAP and LIME Python Libraries - Using SHAP & LIME with XGBoost
IRESpy: an XGBoost model for prediction of internal ribosome entry sites | BMC Bioinformatics | Full Text
Results of LIME with XGBoost and Random Forest classifiers applied to... | Download Scientific Diagram
LIME Loop Nodes with a Custom Regression Model – KNIME Community Hub
How to Interpret Black Box Models using LIME (Local Interpretable Model-Agnostic Explanations)
Building Trust in Machine Learning Models (using LIME in Python)
How to Interpret Black Box Models using LIME (Local Interpretable Model-Agnostic Explanations)
xgboost - 'lime' package in R intuition - Stack Overflow
Application of interpretable machine learning for early prediction of prognosis in acute kidney injury - ScienceDirect
Interpreting an NLP model with LIME and SHAP | by Kalia Barkai | Medium
How to Convince Your Boss to Trust Your ML/DL Models | by Gurami Keretchashvili | Towards Data Science
Explaining Machine Learning Classifiers with LIME – Random experiments in software engineering
Explaining Machine Learning Classifiers with LIME – Random experiments in software engineering
How to Interpret Machine Learning Models with LIME and SHAP
Brain Sciences | Free Full-Text | Interpretable Machine Learning Model Predicting Early Neurological Deterioration in Ischemic Stroke Patients Treated with Mechanical Thrombectomy: A Retrospective Study
Explaining Black-Box Machine Learning Models – Code Part 2: Text classification with LIME | R-bloggers
Explainable Artificial Intelligence Model for Stroke Prediction Using EEG Signal
SHAP and LIME: Great ML Explainers with Pros and Cons to Both
Visualizing ML Models with LIME · UC Business Analytics R Programming Guide
LIME results with XGBoost classifiers used for two patients with... | Download Scientific Diagram
Data Science For Business Tutorial: Using Machine Learning With LIME To Understand Employee Churn | R-bloggers
