SOTAVerified

Feature Importance

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 576–600 of 890 papers

TitleStatusHype
A Dynamic-Adversarial Mining Approach to the Security of Machine Learning—0
AEFE: Automatic Embedded Feature Engineering for Categorical Features—0
A Feature Importance Analysis for Soft-Sensing-Based Predictions in a Chemical Sulphonation Process—0
A Framework for Constructing Machine Learning Models with Feature Set Optimisation for Evapotranspiration Partitioning—0
A Graph Neural Network deep-dive into successful counterattacks—0
A Hybrid Deep Learning-based Approach for Optimal Genotype by Environment Selection—0
A hybrid supervised/unsupervised machine learning approach to solar flare prediction—0
AI Data Readiness Inspector (AIDRIN) for Quantitative Assessment of Data Readiness for AI—0
Algorithm-Agnostic Interpretations for Clustering—0
Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales—0
A Linguistic Perspective on Reference: Choosing a Feature Set for Generating Referring Expressions in Context—0
AltFS: Agency-light Feature Selection with Large Language Models in Deep Recommender Systems—0
A machine learning approach to predict the structural and magnetic properties of Heusler alloy families—0
A matching based clustering algorithm for categorical data—0
A Multi-Head Attention Soft Random Forest for Interpretable Patient No-Show Prediction—0
A Multi-Task Text Classification Pipeline with Natural Language Explanations: A User-Centric Evaluation in Sentiment Analysis and Offensive Language Identification in Greek Tweets—0
An AI-driven framework for rapid and localized optimizations of urban open spaces—0
Analysis of Zero Day Attack Detection Using MLP and XAI—0
Analyze Additive and Interaction Effects via Collaborative Trees—0
Analyzing Domestic Violence through Exploratory Data Analysis and Explainable Ensemble Learning Insights—0
An Approach To Enhance IoT Security In 6G Networks Through Explainable AI—0
An Automatic Relevance Determination Prior Bayesian Neural Network for Controlled Variable Selection—0
An Efficient Row-Based Sparse Fine-Tuning—0
An Evaluation of Zero-Cost Proxies -- from Neural Architecture Performance to Model Robustness—0
An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.76—Unverified
2Garson Variable ImportancePearson 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