SOTAVerified

Feature Importance

Papers

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Showing 376–400 of 890 papers

TitleStatusHype
Error-controlled non-additive interaction discovery in machine learning models—0
Error-based Knockoffs Inference for Controlled Feature Selection—0
Feature Importance Guided Attack: A Model Agnostic Adversarial Attack—0
Feature Importance in a Deep Learning Climate Emulator—0
Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection—0
Feature Importance in Pedestrian Intention Prediction: A Context-Aware Review—0
Risk-Adjusted Performance of Random Forest Models in High-Frequency Trading—0
Building Trust in Black-box Optimization: A Comprehensive Framework for Explainability—0
Ensembling improves stability and power of feature selection for deep learning models—0
An Evaluation of Zero-Cost Proxies -- from Neural Architecture Performance to Model Robustness—0
Feature importance recap and stacking models for forex price prediction—0
Feature importance scores and lossless feature pruning using Banzhaf power indices—0
COVID-19 diagnosis by routine blood tests using machine learning—0
CaliciBoost: Performance-Driven Evaluation of Molecular Representations for Caco-2 Permeability Prediction—0
Crash Severity Risk Modeling Strategies under Data Imbalance—0
Crop yield probability density forecasting via quantile random forest and Epanechnikov Kernel function—0
Feature Selection for Discovering Distributional Treatment Effect Modifiers—0
Feature Selection for Imbalanced Data with Deep Sparse Autoencoders Ensemble—0
Feature Selection via GANs (GANFS): Enhancing Machine Learning Models for DDoS Mitigation—0
Federated unsupervised random forest for privacy-preserving patient stratification—0
FedSDG-FS: Efficient and Secure Feature Selection for Vertical Federated Learning—0
Enriching Tabular Data with Contextual LLM Embeddings: A Comprehensive Ablation Study for Ensemble Classifiers—0
AltFS: Agency-light Feature Selection with Large Language Models in Deep Recommender Systems—0
Enhancing Phishing Detection through Feature Importance Analysis and Explainable AI: A Comparative Study of CatBoost, XGBoost, and EBM Models—0
Building Matters: Spatial Variability in Machine Learning Based Thermal Comfort Prediction in Winters—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