Hacker News
- Why the discrepancy between predict.xgb.Booster & xgboostexplainer prediction contributions? http://blog.datadive.net/interpreting-random-forests/ 7 comments rstats
Linking pages
- GitHub - slundberg/shap: A game theoretic approach to explain the output of any machine learning model. https://github.com/slundberg/shap 20 comments
- GitHub - EthicalML/awesome-production-machine-learning: A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning https://github.com/EthicalML/awesome-production-machine-learning 0 comments
- Interpretable Machine Learning with Python - Savvas Tjortjoglou http://savvastjortjoglou.com/intrepretable-machine-learning-nfl-combine.html 0 comments
- Black box interpretations | Dasha.AI https://dasha.ai/en-us/blog/black-box-interpretations-ml 0 comments
- How To Get Feature Importance in Random Forests | Forecastegy https://forecastegy.com/posts/feature-importance-in-random-forests/ 0 comments
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