SOTAVerified

Feature Importance

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–300 of 890 papers

TitleStatusHype
Hierarchical Symbolic Reasoning in Hyperbolic Space for Deep Discriminative ModelsCode0
Sobolev Independence CriterionCode0
Exclusion and Inclusion -- A model agnostic approach to feature importance in DNNsCode0
Captum: A unified and generic model interpretability library for PyTorchCode0
Hierarchical clustering: visualization, feature importance and model selectionCode0
Can local explanation techniques explain linear additive models?Code0
Granger-causal Attentive Mixtures of Experts: Learning Important Features with Neural NetworksCode0
GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution DetectionCode0
Evaluating Model Explanations without Ground TruthCode0
GLANCE: Global to Local Architecture-Neutral Concept-based ExplanationsCode0
Handling Missing Values in Local Post-hoc ExplainabilityCode0
FIMBA: Evaluating the Robustness of AI in Genomics via Feature Importance Adversarial AttacksCode0
An Explainable Pipeline for Machine Learning with Functional DataCode0
FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example GenerationCode0
Feature Selection and Feature Extraction in Pattern Analysis: A Literature ReviewCode0
eSports Pro-Players Behavior During the Game Events: Statistical Analysis of Data Obtained Using the Smart ChairCode0
A Genre-Aware Attention Model to Improve the Likability Prediction of BooksCode0
Variable Importance Matching for Causal InferenceCode0
Feature Importance Measurement based on Decision Tree SamplingCode0
EPIC: Explanation of Pretrained Image Classification Networks via PrototypeCode0
AFS-BM: Enhancing Model Performance through Adaptive Feature Selection with Binary MaskingCode0
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal ExplanationCode0
FAT-DeepFFM: Field Attentive Deep Field-aware Factorization MachineCode0
Feature Importance and Explainability in Quantum Machine LearningCode0
An Evaluation of Explanation Methods for Black-Box Detectors of Machine-Generated TextCode0
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
Show:102550
← PrevPage 6 of 18Next →
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