SOTAVerified

Feature Importance

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–375 of 890 papers

TitleStatusHype
Machine Learning Assessment of Damage Grade for Post-Earthquake Buildings: A Three-Stage Approach Directly Handling Categorical FeaturesCode0
TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection—0
MvFS: Multi-view Feature Selection for Recommender SystemCode1
Calibrated Explanations for RegressionCode1
Causality-Based Feature Importance Quantifying Methods: PN-FI, PS-FI and PNS-FI—0
MMBAttn: Max-Mean and Bit-wise Attention for CTR Prediction—0
Predicting Drug Solubility Using Different Machine Learning Methods -- Linear Regression Model with Extracted Chemical Features vs Graph Convolutional Neural Network—0
An interpretable deep learning method for bearing fault diagnosis—0
ChatGPT-HealthPrompt. Harnessing the Power of XAI in Prompt-Based Healthcare Decision Support using ChatGPTCode0
A coupled-mechanisms modelling framework for neurodegeneration—0
Semantic Interpretation and Validation of Graph Attention-based Explanations for GNN Models—0
Feature Importance versus Feature Influence and What It Signifies for Explainable AI—0
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke—0
Confident Feature RankingCode0
Turning hazardous volatile matter compounds into fuel by catalytic steam reforming: An evolutionary machine learning approach—0
Feature Importance Measurement based on Decision Tree SamplingCode0
FairMobi-Net: A Fairness-aware Deep Learning Model for Urban Mobility Flow Generation—0
Beyond Single-Feature Importance with ICECREAM—0
An Evaluation of Zero-Cost Proxies -- from Neural Architecture Performance to Model Robustness—0
Explaining and visualizing black-box models through counterfactual pathsCode0
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations—0
SHAP@k:Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features—0
Predicting Outcomes in Long COVID Patients with Spatiotemporal Attention—0
On Formal Feature Attribution and Its ApproximationCode0
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning BenchmarksCode1
Show:102550
← PrevPage 15 of 36Next →
All datasetsbostonBreastcancerDiabetesDigitsirisWine

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