SOTAVerified

Feature Importance

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–225 of 890 papers

TitleStatusHype
Efficient Interpretation of Deep Learning Models Using Graph Structure and Cooperative Game Theory: Application to ASD Biomarker Discovery—0
Data-driven Prediction of Relevant Scenarios for Robust Combinatorial Optimization—0
Data-Driven Transient Stability Assessment of Power Systems with a Novel GHM-Enhanced CatBoost Algorithm—0
Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders—0
Data Model Design for Explainable Machine Learning-based Electricity Applications—0
Data Strategies for Fleetwide Predictive Maintenance—0
Comparing Explanation Methods for Traditional Machine Learning Models Part 1: An Overview of Current Methods and Quantifying Their Disagreement—0
COMIX: Compositional Explanations using Prototypes—0
On The Impact of Merge Request Deviations on Code Review Practices—0
A matching based clustering algorithm for categorical data—0
Efficient Milling Quality Prediction with Explainable Machine Learning—0
Learning Interpretable Characteristic Kernels via Decision Forests—0
Interpreting Criminal Charge Prediction and Its Algorithmic Bias via Quantum-Inspired Complex Valued Networks—0
Evaluating Spoken Language as a Biomarker for Automated Screening of Cognitive Impairment—0
Cognitive Networks and Performance Drive fMRI-Based State Classification Using DNN Models—0
Deep learning generates custom-made logistic regression models for explaining how breast cancer subtypes are classified—0
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
Dementia Classification Using Acoustic Speech and Feature Selection—0
Democratizing Evaluation of Deep Model Interpretability through Consensus—0
WheaCha: A Method for Explaining the Predictions of Models of Code—0
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks—0
Clustering of Disease Trajectories with Explainable Machine Learning: A Case Study on Postoperative Delirium Phenotypes—0
A Pipeline for Data-Driven Learning of Topological Features with Applications to Protein Stability Prediction—0
A Multi-Head Attention Soft Random Forest for Interpretable Patient No-Show Prediction—0
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data—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