SHAP
SHAP explained the way I wish someone explained it to me
SHAP — which stands for SHapley Additive exPlanations — is probably the state of the art in Machine Learning explainability. This algorithm was first published in 2017 by Lundberg and Lee (here is…
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SHAP (SHapley Additive exPlanations)
SHAP (SHapley Additive exPlanations) by Lundberg and Lee (2017) 69 is a method to explain individual predictions. SHAP is based on the game theoretically optimal Shapley values . There are two reasons...
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SHAP Part 3: Tree SHAP
Tree SHAP is an algorithm to compute exact SHAP values for Decision Trees based models. SHAP (SHapley Additive exPlanation) is a game theoretic approach to explain the output of any machine learning…
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June Edition: Get into SHAP
The ins and outs of a powerful explainable-AI approach Photo by Héctor J. Rivas on Unsplash The power and size of machine learning models have grown to new heights in recent years. With greater compl...
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Four Custom SHAP Plots
SHAP values are a great tool for understanding how a model makes predictions. The SHAP package provides many visualisations that make this process even easier. That being said, we do not have to rely…...
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Geographic SHAP
"R Python" continued... Geographic SHAP Continue reading: Geographic SHAP
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Analysing Interactions with SHAP
SHAP values are used to explain individual predictions made by a model. It does this by giving the contributions of each factor to the final prediction. SHAP interaction values extend on this by…
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Explain ML models : SHAP Library
SHAP in other words (Shapley Additive Explanations) is a tool used to understand how your model predicts in a certain way. In my last blog, I tried to explain the importance of interpreting our…
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SHAP Values
Introduction You've seen (and used) techniques to extract general insights from a machine learning model. But what if you want to break down how the model works for an individual prediction? SHAP Val...
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SHAP Values
Introduction You've seen (and used) techniques to extract general insights from a machine learning model. But what if you want to break down how the model works for an individual prediction? SHAP Val...
📚 Read more at Kaggle Learn Courses🔎 Find similar documents
SHAP Values
Introduction You've seen (and used) techniques to extract general insights from a machine learning model. But what if you want to break down how the model works for an individual prediction? SHAP Val...
📚 Read more at Kaggle Learn Courses🔎 Find similar documents
SHAP for Drift Detection: Effective Data Shift Monitoring
Alerting Distribution Divercences using Model Knowledge Continue reading on Towards Data Science
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