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Feature Importance

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 276–300 of 890 papers

TitleStatusHype
A Comparative Approach to Explainable Artificial Intelligence Methods in Application to High-Dimensional Electronic Health Records: Examining the Usability of XAI—0
Abstract Interpretation-Based Feature Importance for SVMs—0
Explaining the Unexplained: Revealing Hidden Correlations for Better Interpretability—0
A Notion of Feature Importance by Decorrelation and Detection of Trends by Random Forest Regression—0
Explaining Data-Driven Decisions made by AI Systems: The Counterfactual Approach—0
Examining Uniqueness and Permanence of the WAY EEG GAL dataset toward User Authentication—0
Explaining Deep Learning-based Anomaly Detection in Energy Consumption Data by Focusing on Contextually Relevant Data—0
Explaining Humour Style Classifications: An XAI Approach to Understanding Computational Humour Analysis—0
An interpretable deep learning method for bearing fault diagnosis—0
Evaluating the Determinants of Mode Choice Using Statistical and Machine Learning Techniques in the Indian Megacity of Bengaluru—0
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke—0
A Graph Neural Network deep-dive into successful counterattacks—0
Evaluating the Correctness of Explainable AI Algorithms for Classification—0
Evaluating Spoken Language as a Biomarker for Automated Screening of Cognitive Impairment—0
Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Paths—0
An exploration of features to improve the generalisability of fake news detection models—0
AcME-AD: Accelerated Model Explanations for Anomaly Detection—0
Evaluation of Feature-based explanations—0
Evaluating Local Explanations using White-box Models—0
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition—0
LEAFAGE: Example-based and Feature importance-based Explanationsfor Black-box ML models—0
Capturing Momentum: Tennis Match Analysis Using Machine Learning and Time Series Theory—0
Anomaly Detection in Power Generation Plants with Generative Adversarial Networks—0
Explaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance—0
Explaining Time Series by Counterfactuals—0
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Benchmark Results

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