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Feature Importance

Papers

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Showing 101–150 of 890 papers

TitleStatusHype
RISE: Randomized Input Sampling for Explanation of Black-box ModelsCode1
Hierarchical interpretations for neural network predictionsCode1
A Unified Approach to Interpreting Model PredictionsCode1
MUPAX: Multidimensional Problem Agnostic eXplainable AI—0
Neural Network-Guided Symbolic Regression for Interpretable Descriptor Discovery in Perovskite Catalysts—0
SentiDrop: A Multi Modal Machine Learning model for Predicting Dropout in Distance Learning—0
Feature-Guided Neighbor Selection for Non-Expert Evaluation of Model Predictions—0
Segment Anything in Pathology Images with Natural Language—0
The Role of Explanation Styles and Perceived Accuracy on Decision Making in Predictive Process Monitoring—0
Enhancing interpretability of rule-based classifiers through feature graphsCode0
Correlation vs causation in Alzheimer's disease: an interpretability-driven study—0
Local MDI+: Local Feature Importances for Tree-Based Models—0
On The Impact of Merge Request Deviations on Code Review Practices—0
Profiling Electric Vehicles via Early Charging Voltage PatternsCode0
Towards Large Language Models with Self-Consistent Natural Language Explanations—0
CaliciBoost: Performance-Driven Evaluation of Molecular Representations for Caco-2 Permeability Prediction—0
Causal Explainability of Machine Learning in Heart Failure Prediction from Electronic Health Records—0
The Reader is the Metric: How Textual Features and Reader Profiles Explain Conflicting Evaluations of AI Creative WritingCode0
Spatial Association Between Near-Misses and Accident Blackspots in Sydney, Australia: A Getis-Ord G_i^* Analysis—0
Multi-criteria Rank-based Aggregation for Explainable AICode0
Dual-Task Graph Neural Network for Joint Seizure Onset Zone Localization and Outcome Prediction using Stereo EEG—0
Data Model Design for Explainable Machine Learning-based Electricity Applications—0
Response Uncertainty and Probe Modeling: Two Sides of the Same Coin in LLM Interpretability?—0
A Multi-Head Attention Soft Random Forest for Interpretable Patient No-Show Prediction—0
Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals—0
EPIC: Explanation of Pretrained Image Classification Networks via PrototypeCode0
FRAME-C: A knowledge-augmented deep learning pipeline for classifying multi-electrode array electrophysiological signals—0
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data AugmentationCode0
Semantically-Aware Game Image Quality Assessment—0
Real-World fNIRS-Based Brain-Computer Interfaces: Benchmarking Deep Learning and Classical Models in Interactive Gaming—0
Financial Fraud Detection Using Explainable AI and Stacking Ensemble Methods—0
Evaluating Model Explanations without Ground TruthCode0
QuXAI: Explainers for Hybrid Quantum Machine Learning ModelsCode0
Optimizing Urban Critical Green Space Development Using Machine Learning—0
SHAP-based Explanations are Sensitive to Feature RepresentationCode0
Integrating Natural Language Processing and Exercise Monitoring for Early Diagnosis of Metabolic Syndrome: A Deep Learning Approach—0
Machine Learning-Based Detection of DDoS Attacks in VANETs for Emergency Vehicle Communication—0
BMMDetect: A Multimodal Deep Learning Framework for Comprehensive Biomedical Misconduct Detection—0
This part looks alike this: identifying important parts of explained instances and prototypesCode0
Detecting Quishing Attacks with Machine Learning Techniques Through QR Code AnalysisCode0
Unemployment Dynamics Forecasting with Machine Learning Regression Models—0
Multi-Hierarchical Fine-Grained Feature Mapping Driven by Feature Contribution for Molecular Odor Prediction—0
Machine Learning Meets Transparency in Osteoporosis Risk Assessment: A Comparative Study of ML and Explainability Analysis—0
What's Wrong with Your Synthetic Tabular Data? Using Explainable AI to Evaluate Generative ModelsCode0
Interpretable machine learning-guided design of Fe-based soft magnetic alloys—0
Explainable Deep-Learning Based Potentially Hazardous Asteroids Classification Using Graph Neural NetworksCode0
Machine Learning Interpretation of Optical Spectroscopy Using Peak-Sensitive Logistic RegressionCode0
Explainable Unsupervised Anomaly Detection with Random Forest—0
Feature Selection via GANs (GANFS): Enhancing Machine Learning Models for DDoS Mitigation—0
Investigating cybersecurity incidents using large language models in latest-generation wireless networks—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