[HTML][HTML] Explaining individual predictions when features are dependent: More accurate approximations to Shapley values
Explaining complex or seemingly simple machine learning models is an important practical
problem. We want to explain individual predictions from such models by learning simple …
problem. We want to explain individual predictions from such models by learning simple …
The explanation game: Explaining machine learning models using shapley values
A number of techniques have been proposed to explain a machine learning model's
prediction by attributing it to the corresponding input features. Popular among these are …
prediction by attributing it to the corresponding input features. Popular among these are …
Causal shapley values: Exploiting causal knowledge to explain individual predictions of complex models
Shapley values underlie one of the most popular model-agnostic methods within
explainable artificial intelligence. These values are designed to attribute the difference …
explainable artificial intelligence. These values are designed to attribute the difference …
Problems with Shapley-value-based explanations as feature importance measures
IE Kumar, S Venkatasubramanian… - International …, 2020 - proceedings.mlr.press
Game-theoretic formulations of feature importance have become popular as a way to"
explain" machine learning models. These methods define a cooperative game between the …
explain" machine learning models. These methods define a cooperative game between the …
Shapley Residuals: Quantifying the limits of the Shapley value for explanations
I Kumar, C Scheidegger… - Advances in …, 2021 - proceedings.neurips.cc
Popular feature importance techniques compute additive approximations to nonlinear
models by first defining a cooperative game describing the value of different subsets of the …
models by first defining a cooperative game describing the value of different subsets of the …
On the tractability of SHAP explanations
SHAP explanations are a popular feature-attribution mechanism for explainable AI. They
use game-theoretic notions to measure the influence of individual features on the prediction …
use game-theoretic notions to measure the influence of individual features on the prediction …
Fastshap: Real-time shapley value estimation
Although Shapley values are theoretically appealing for explaining black-box models, they
are costly to calculate and thus impractical in settings that involve large, high-dimensional …
are costly to calculate and thus impractical in settings that involve large, high-dimensional …
The many Shapley values for model explanation
M Sundararajan, A Najmi - International conference on …, 2020 - proceedings.mlr.press
The Shapley value has become the basis for several methods that attribute the prediction of
a machine-learning model on an input to its base features. The use of the Shapley value is …
a machine-learning model on an input to its base features. The use of the Shapley value is …
GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles
Abstract SHapley Additive exPlanation (SHAP) values (Lundberg & Lee, 2017) provide a
game theoretic interpretation of the predictions of machine learning models based on …
game theoretic interpretation of the predictions of machine learning models based on …
Weightedshap: analyzing and improving shapley based feature attributions
Shapley value is a popular approach for measuring the influence of individual features.
While Shapley feature attribution is built upon desiderata from game theory, some of its …
While Shapley feature attribution is built upon desiderata from game theory, some of its …