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Feature Importance

Papers

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Showing 551–600 of 890 papers

TitleStatusHype
Exploring Patterns Behind Sports—0
Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning—0
Facilitating Machine Learning Model Comparison and Explanation Through A Radial Visualisation—0
FACT: High-Dimensional Random Forests Inference—0
FairCanary: Rapid Continuous Explainable Fairness—0
Fair Feature Importance Scores for Interpreting Tree-Based Methods and Surrogates—0
FairMobi-Net: A Fairness-aware Deep Learning Model for Urban Mobility Flow Generation—0
Fair MP-BOOST: Fair and Interpretable Minipatch Boosting—0
Faking feature importance: A cautionary tale on the use of differentially-private synthetic data—0
FAST: Feature Arrangement for Semantic Transmission—0
Fault Detection for agents on power grid topology optimization: A Comprehensive analysis—0
FeatNavigator: Automatic Feature Augmentation on Tabular Data—0
Feature Analyses and Modelling of Lithium-ion Batteries Manufacturing based on Random Forest Classification—0
Feature-Attention Graph Convolutional Networks for Noise Resilient Learning—0
Feature-Guided Neighbor Selection for Non-Expert Evaluation of Model Predictions—0
Feature Importance: A Closer Look at Shapley Values and LOCO—0
Learning to Detect Critical Nodes in Sparse Graphs via Feature Importance Awareness—0
Feature Importance Depends on Properties of the Data: Towards Choosing the Correct Explanations for Your Data and Decision Trees based Models—0
Feature Importance Estimation with Self-Attention Networks—0
Feature Importance for Time Series Data: Improving KernelSHAP—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
Feature Importance of Climate Vulnerability Indicators with Gradient Boosting across Five Global Cities—0
Feature importance recap and stacking models for forex price prediction—0
Feature importance scores and lossless feature pruning using Banzhaf power indices—0
Feature Importance versus Feature Influence and What It Signifies for Explainable AI—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
Financial Fraud Detection Using Explainable AI and Stacking Ensemble Methods—0
Fiper: a Visual-based Explanation Combining Rules and Feature Importance—0
FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning—0
FORCE: Feature-Oriented Representation with Clustering and Explanation—0
Forecasting Automotive Supply Chain Shortfalls with Heterogeneous Time Series—0
Forecasting Corn Yield with Machine Learning Ensembles—0
FORLAPS: An Innovative Data-Driven Reinforcement Learning Approach for Prescriptive Process Monitoring—0
Forma mentis networks predict creativity ratings of short texts via interpretable artificial intelligence in human and GPT-simulated raters—0
FRAME-C: A knowledge-augmented deep learning pipeline for classifying multi-electrode array electrophysiological signals—0
From Predictive Importance to Causality: Which Machine Learning Model Reflects Reality?—0
From SHAP Scores to Feature Importance Scores—0
From unbiased MDI Feature Importance to Explainable AI for Trees—0
Generating Interpretable Poverty Maps using Object Detection in Satellite Images—0
Generative LLM Powered Conversational AI Application for Personalized Risk Assessment: A Case Study in COVID-19—0
GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease—0
Global Censored Quantile Random Forest—0
Grad-FEC: Unequal Loss Protection of Deep Features in Collaborative Intelligence—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