SOTAVerified

Feature Importance

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 226–250 of 890 papers

TitleStatusHype
Multi-LLM QA with Embodied Exploration—0
FeatNavigator: Automatic Feature Augmentation on Tabular Data—0
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare RecordsCode2
Deep reinforcement learning with positional context for intraday trading—0
Learned Feature Importance Scores for Automated Feature Engineering—0
MS-IMAP -- A Multi-Scale Graph Embedding Approach for Interpretable Manifold Learning—0
CAFO: Feature-Centric Explanation on Time Series ClassificationCode1
Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space—0
Model Interpretation and Explainability: Towards Creating Transparency in Prediction Models—0
Explainable Data-driven Modeling of Adsorption Energy in Heterogeneous CatalysisCode0
Unified Explanations in Machine Learning Models: A Perturbation ApproachCode0
I Bet You Did Not Mean That: Testing Semantic Importance via BettingCode0
MCDFN: Supply Chain Demand Forecasting via an Explainable Multi-Channel Data Fusion Network Model—0
Attention Mechanisms Don't Learn Additive Models: Rethinking Feature Importance for TransformersCode0
From SHAP Scores to Feature Importance Scores—0
Exploring Commonalities in Explanation Frameworks: A Multi-Domain Survey Analysis—0
Analyze Additive and Interaction Effects via Collaborative Trees—0
Mitigating Text Toxicity with Counterfactual Generation—0
Feature Importance and Explainability in Quantum Machine LearningCode0
Clustering of Disease Trajectories with Explainable Machine Learning: A Case Study on Postoperative Delirium Phenotypes—0
Estimate the building height at a 10-meter resolution based on Sentinel data—0
Feature importance to explain multimodal prediction models. A clinical use caseCode0
DTization: A New Method for Supervised Feature Scaling—0
Accurate and fast anomaly detection in industrial processes and IoT environments—0
Optimizing Universal Lesion Segmentation: State Space Model-Guided Hierarchical Networks with Feature Importance Adjustment—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