Explaining the output of machine learning models with more accurately estimated Shapley values
The complex nature of artificial neural networks raises concerns on their reliability, trustworthine...
International audienceA number of techniques have been proposed to explain a machine learning model’...
We have seen complex deep learning models outperforming human benchmarks in many areas (e.g. compute...
The Shapley value method is an explanatory method that describes the feature attribution of Machine ...
This paper documents published code which can help facilitate researchers with binary classification...
Shapley value -- a useful way to allocate gains in cooperative games -- has been very successful in ...
Over the last few years, the Shapley value, a solution concept from cooperative game theory, has fou...
Practical Machine Learning with R gives you the complete knowledge to solve your business problems -...
Praca dotyczy wartości Shapleya w dwóch różnych dziedzinach: teorii gier oraz uczeniu maszynowym. Pi...
Interpretability of learning algorithms is crucial for applications involving critical decisions, an...
Explainability of machine learning models is increasing in importance. The reason for this is that t...
Interpretability methods to analyze the behavior and predictions of any machine learning model. Impl...
The evaluation results based on four simple machine learning models for two datasets.</p
22 pagesMany machine learning problems require performing dataset valuation, i.e. to quantify the in...
International audienceIt is becoming increasingly important to explain complex, black-box machine le...
The complex nature of artificial neural networks raises concerns on their reliability, trustworthine...
International audienceA number of techniques have been proposed to explain a machine learning model’...
We have seen complex deep learning models outperforming human benchmarks in many areas (e.g. compute...
The Shapley value method is an explanatory method that describes the feature attribution of Machine ...
This paper documents published code which can help facilitate researchers with binary classification...
Shapley value -- a useful way to allocate gains in cooperative games -- has been very successful in ...
Over the last few years, the Shapley value, a solution concept from cooperative game theory, has fou...
Practical Machine Learning with R gives you the complete knowledge to solve your business problems -...
Praca dotyczy wartości Shapleya w dwóch różnych dziedzinach: teorii gier oraz uczeniu maszynowym. Pi...
Interpretability of learning algorithms is crucial for applications involving critical decisions, an...
Explainability of machine learning models is increasing in importance. The reason for this is that t...
Interpretability methods to analyze the behavior and predictions of any machine learning model. Impl...
The evaluation results based on four simple machine learning models for two datasets.</p
22 pagesMany machine learning problems require performing dataset valuation, i.e. to quantify the in...
International audienceIt is becoming increasingly important to explain complex, black-box machine le...
The complex nature of artificial neural networks raises concerns on their reliability, trustworthine...
International audienceA number of techniques have been proposed to explain a machine learning model’...
We have seen complex deep learning models outperforming human benchmarks in many areas (e.g. compute...
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