SOTAVerified

Feature Importance

Papers

Showing 101125 of 890 papers

TitleStatusHype
Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responsesCode1
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for AutoencodersCode1
A Unified Approach to Interpreting Model PredictionsCode1
AEFE: Automatic Embedded Feature Engineering for Categorical Features0
Accurate estimation of feature importance faithfulness for tree models0
Comparing Explanation Methods for Traditional Machine Learning Models Part 1: An Overview of Current Methods and Quantifying Their Disagreement0
Analyze Additive and Interaction Effects via Collaborative Trees0
A Dynamic-Adversarial Mining Approach to the Security of Machine Learning0
COMIX: Compositional Explanations using Prototypes0
Comparing Explanation Methods for Traditional Machine Learning Models Part 2: Quantifying Model Explainability Faithfulness and Improvements with Dimensionality Reduction0
Correlation vs causation in Alzheimer's disease: an interpretability-driven study0
Axiomatic Aggregations of Abductive Explanations0
A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization0
A Multi-Task Text Classification Pipeline with Natural Language Explanations: A User-Centric Evaluation in Sentiment Analysis and Offensive Language Identification in Greek Tweets0
Clustering of Disease Trajectories with Explainable Machine Learning: A Case Study on Postoperative Delirium Phenotypes0
Accurate and Robust Feature Importance Estimation under Distribution Shifts0
An AI-driven framework for rapid and localized optimizations of urban open spaces0
Automatic prediction of mortality in patients with mental illness using electronic health records0
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability0
Analysis of Zero Day Attack Detection Using MLP and XAI0
Enhanced Prediction of Ventilator-Associated Pneumonia in Patients with Traumatic Brain Injury Using Advanced Machine Learning Techniques0
Better Model Selection with a new Definition of Feature Importance0
Analyzing Domestic Violence through Exploratory Data Analysis and Explainable Ensemble Learning Insights0
Beyond Feature Importance: Feature Interactions in Predicting Post-Stroke Rigidity with Graph Explainable AI0
Automatic Componentwise Boosting: An Interpretable AutoML System0
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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