SOTAVerified

Feature Importance

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 626–650 of 890 papers

TitleStatusHype
A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization—0
Axiomatic Aggregations of Abductive Explanations—0
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability—0
Benchmarking the Fidelity and Utility of Synthetic Relational Data—0
Better Model Selection with a new Definition of Feature Importance—0
Beyond Feature Importance: Feature Interactions in Predicting Post-Stroke Rigidity with Graph Explainable AI—0
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics—0
Beyond Single-Feature Importance with ICECREAM—0
Bias Reducing Multitask Learning on Mental Health Prediction—0
BiT-MamSleep: Bidirectional Temporal Mamba for EEG Sleep Staging—0
BMMDetect: A Multimodal Deep Learning Framework for Comprehensive Biomedical Misconduct Detection—0
Building effective deep neural network architectures one feature at a time—0
Building effective deep neural networks one feature at a time—0
Building Matters: Spatial Variability in Machine Learning Based Thermal Comfort Prediction in Winters—0
Building Trust in Black-box Optimization: A Comprehensive Framework for Explainability—0
CAGE: Causality-Aware Shapley Value for Global Explanations—0
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke—0
Capturing Momentum: Tennis Match Analysis Using Machine Learning and Time Series Theory—0
CatNet: Controlling the False Discovery Rate in LSTM with SHAP Feature Importance and Gaussian Mirrors—0
Causal Explainability of Machine Learning in Heart Failure Prediction from Electronic Health Records—0
Causality-Based Feature Importance Quantifying Methods: PN-FI, PS-FI and PNS-FI—0
CFMD: Dynamic Cross-layer Feature Fusion for Salient Object Detection—0
CGS-Mask: Making Time Series Predictions Intuitive for All—0
Channel Pruning Guided by Classification Loss and Feature Importance—0
Characterizing climate pathways using feature importance on echo state networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.76—Unverified
2Garson Variable ImportancePearson 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