SOTAVerified

Feature Importance

Papers

Showing 76100 of 890 papers

TitleStatusHype
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetCode1
Shapley Flow: A Graph-based Approach to Interpreting Model PredictionsCode1
Benchmarking Deep Learning Interpretability in Time Series PredictionsCode1
Measuring Association Between Labels and Free-Text RationalesCode1
Feature Importance Ranking for Deep LearningCode1
Understanding Information Processing in Human Brain by Interpreting Machine Learning ModelsCode1
Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction TaskCode1
agtboost: Adaptive and Automatic Gradient Tree Boosting ComputationsCode1
Reliable Post hoc Explanations: Modeling Uncertainty in ExplainabilityCode1
Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature ImportanceCode1
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning ModelsCode1
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation VectorsCode1
Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data AugmentationCode1
Efficient nonparametric statistical inference on population feature importance using Shapley valuesCode1
Nonparametric Feature Impact and ImportanceCode1
DBA: Distributed Backdoor Attacks against Federated LearningCode1
Learning to Faithfully Rationalize by ConstructionCode1
Understanding Global Feature Contributions With Additive Importance MeasuresCode1
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAICode1
A Matlab Toolbox for Feature Importance RankingCode1
Explainability and Adversarial Robustness for RNNsCode1
FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate PredictionCode1
Disentangled Attribution Curves for Interpreting Random Forests and Boosted TreesCode1
Interpret Federated Learning with Shapley ValuesCode1
Interpretable machine learning: definitions, methods, and applicationsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Garson Variable ImportancePearson Correlation0.76Unverified
2VarImpVIANNPearson Correlation0.76Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.6Unverified
2Garson Variable ImportancePearson Correlation0.22Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.86Unverified
2Garson Variable ImportancePearson Correlation0.64Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.83Unverified
2Garson Variable ImportancePearson Correlation0.6Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.9Unverified
2Garson Variable ImportancePearson Correlation0.73Unverified
#ModelMetricClaimedVerifiedStatus
1Garson Variable ImportancePearson Correlation0.74Unverified
2VarImpVIANNPearson Correlation0.41Unverified