SOTAVerified

Feature Importance

Papers

Showing 276300 of 890 papers

TitleStatusHype
Nonparametric IPSS: Fast, flexible feature selection with false discovery controlCode0
Feature importance to explain multimodal prediction models. A clinical use caseCode0
Feature Importance Measure for Non-linear Learning AlgorithmsCode0
From Feature Importance to Natural Language Explanations Using LLMs with RAGCode0
Enhancing interpretability of rule-based classifiers through feature graphsCode0
An ensemble meta-estimator to predict source code testabilityCode0
Feature Responsiveness Scores: Model-Agnostic Explanations for RecourseCode0
Explanation by Progressive ExaggerationCode0
Evaluating Explainable Methods for Predictive Process Analytics: A Functionally-Grounded ApproachCode0
A Benchmark for Interpretability Methods in Deep Neural NetworksCode0
Calculating and Visualizing Counterfactual Feature Importance ValuesCode0
Explain to Fix: A Framework to Interpret and Correct DNN Object Detector PredictionsCode0
BrainMetDetect: Predicting Primary Tumor from Brain Metastasis MRI Data Using Radiomic Features and Machine Learning AlgorithmsCode0
Extensive Evaluation of Transformer-based Architectures for Adverse Drug Events ExtractionCode0
End-to-end Feature Selection Approach for Learning Skinny TreesCode0
BMX: Boosting Natural Language Generation Metrics with ExplainabilityCode0
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input FeaturesCode0
Explainable Post hoc Portfolio Management Financial Policy of a Deep Reinforcement Learning agentCode0
Graph machine learning for flight delay prediction due to holding manouverCode0
Explaining word embeddings with perfect fidelity: Case study in research impact predictionCode0
Elastic Net based Feature Ranking and SelectionCode0
Explainable Debugger for Black-box Machine Learning ModelsCode0
Enhancing Interpretability and Generalizability in Extended Isolation ForestsCode0
Explainable Deep-Learning Based Potentially Hazardous Asteroids Classification Using Graph Neural NetworksCode0
EFI: A Toolbox for Feature Importance Fusion and Interpretation in PythonCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Garson Variable ImportancePearson Correlation0.76Unverified
2VarImpVIANNPearson Correlation0.76Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.6Unverified
2Garson Variable ImportancePearson Correlation0.22Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.86Unverified
2Garson Variable ImportancePearson Correlation0.64Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.83Unverified
2Garson Variable ImportancePearson Correlation0.6Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.9Unverified
2Garson Variable ImportancePearson Correlation0.73Unverified
#ModelMetricClaimedVerifiedStatus
1Garson Variable ImportancePearson Correlation0.74Unverified
2VarImpVIANNPearson Correlation0.41Unverified