SOTAVerified

Feature Importance

Papers

Showing 176200 of 890 papers

TitleStatusHype
Classification of cotton water stress using convolutional neural networks and UAV-based RGB imageryCode0
Explainable AI through a Democratic Lens: DhondtXAI for Proportional Feature Importance Using the D'Hondt MethodCode0
Computationally Efficient Feature Significance and Importance for Machine Learning ModelsCode0
Explaining and visualizing black-box models through counterfactual pathsCode0
Conditional Feature Importance for Mixed DataCode0
Conditional Feature Importance with Generative Modeling Using Adversarial Random ForestsCode0
Confident Feature RankingCode0
A novel stacking framework based on hybrid of gradient boosting-adaptive boosting-multilayer perceptron for crash injury severity prediction and analysisCode0
Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based MethodsCode0
A copula-based visualization technique for a neural networkCode0
Choose Your Explanation: A Comparison of SHAP and GradCAM in Human Activity RecognitionCode0
Explainability of Machine Learning Models under Missing DataCode0
Explainable Data-driven Modeling of Adsorption Energy in Heterogeneous CatalysisCode0
Feature importance to explain multimodal prediction models. A clinical use caseCode0
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language ModelsCode0
Explainable Post hoc Portfolio Management Financial Policy of a Deep Reinforcement Learning agentCode0
FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example GenerationCode0
ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPTCode0
A novel post-hoc explanation comparison metric and applicationsCode0
Evaluating Model Explanations without Ground TruthCode0
GLANCE: Global to Local Architecture-Neutral Concept-based ExplanationsCode0
A tree-based varying coefficient modelCode0
CXPlain: Causal Explanations for Model Interpretation under UncertaintyCode0
Evaluating Explainable Methods for Predictive Process Analytics: A Functionally-Grounded ApproachCode0
A Benchmark for Interpretability Methods in Deep Neural NetworksCode0
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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