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Feature Importance

Papers

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Showing 301–350 of 890 papers

TitleStatusHype
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
Personalized Decision Supports based on Theory of Mind Modeling and Explainable Reinforcement Learning—0
Anytime Approximate Formal Feature Attribution—0
A novel feature selection framework for incomplete data—0
CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation ModelsCode1
Class-Discriminative Attention Maps for Vision Transformers—0
Predicting Postoperative Nausea And Vomiting Using Machine Learning: A Model Development and Validation StudyCode0
Enhancing Explainability in Mobility Data Science through a combination of methods—0
Data-Driven Modelling for Harmonic Current Emission in Low-Voltage Grid Using MCReSANet with Interpretability Analysis—0
Towards Auditing Large Language Models: Improving Text-based Stereotype Detection—0
Neural Network Pruning by Gradient DescentCode0
Sweetwater: An interpretable and adaptive autoencoder for efficient tissue deconvolutionCode1
A novel post-hoc explanation comparison metric and applicationsCode0
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution DetectionCode0
Iterative missing value imputation based on feature importance—0
Predicting the First Response Latency of Maintainers and Contributors in Pull Requests—0
Uncertainty estimation of machine learning spatial precipitation predictions from satellite data—0
Transformer-based nowcasting of radar composites from satellite images for severe weatherCode1
Popularity, face and voice: Predicting and interpreting livestreamers' retail performance using machine learning techniques—0
CrossEAI: Using Explainable AI to generate better bounding boxes for Chest X-ray images—0
End-to-end Feature Selection Approach for Learning Skinny TreesCode0
Hierarchical Ensemble-Based Feature Selection for Time Series Forecasting—0
Inside the black box: Neural network-based real-time prediction of US recessions—0
On the stability, correctness and plausibility of visual explanation methods based on feature importance—0
Climate Change Impact on Agricultural Land Suitability: An Interpretable Machine Learning-Based Eurasia Case StudyCode0
Local Universal Explainer (LUX) -- a rule-based explainer with factual, counterfactual and visual explanationsCode1
Handling Missing Values in Local Post-hoc ExplainabilityCode0
On Feature Importance and Interpretability of Speaker Representations—0
Model-agnostic variable importance for predictive uncertainty: an entropy-based approachCode0
Automatic prediction of mortality in patients with mental illness using electronic health records—0
DANAA: Towards transferable attacks with double adversarial neuron attributionCode0
Characterizing climate pathways using feature importance on echo state networks—0
Using Spark Machine Learning Models to Perform Predictive Analysis on Flight Ticket Pricing Data—0
Enhancing Interpretability and Generalizability in Extended Isolation ForestsCode0
LIPEx-Locally Interpretable Probabilistic Explanations-To Look Beyond The True Class—0
Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates—0
Less is More: On the Feature Redundancy of Pretrained Models When Transferring to Few-shot Tasks—0
ML4EJ: Decoding the Role of Urban Features in Shaping Environmental Injustice Using Interpretable Machine Learning—0
Modality-aware Transformer for Financial Time series Forecasting—0
Anomaly Detection in Power Generation Plants with Generative Adversarial Networks—0
Axiomatic Aggregations of Abductive Explanations—0
Tell Me a Story! Narrative-Driven XAI with Large Language ModelsCode0
Explainable machine learning-based prediction model for diabetic nephropathy—0
Machine Learning Based Analytics for the Significance of Gait Analysis in Monitoring and Managing Lower Extremity Injuries—0
Physics Inspired Hybrid Attention for SAR Target RecognitionCode1
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelsCode1
Visualizing Topological Importance: A Class-Driven Approach—0
Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation—0
A Hybrid Deep Learning-based Approach for Optimal Genotype by Environment Selection—0
Can local explanation techniques explain linear additive models?Code0
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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