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Feature Importance

Papers

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Showing 101–150 of 890 papers

TitleStatusHype
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning BenchmarksCode1
WinTSR: A Windowed Temporal Saliency Rescaling Method for Interpreting Time Series Deep Learning ModelsCode1
TimeSHAP: Explaining Recurrent Models through Sequence PerturbationsCode1
AEFE: Automatic Embedded Feature Engineering for Categorical Features—0
Accurate estimation of feature importance faithfulness for tree models—0
Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling—0
Data Model Design for Explainable Machine Learning-based Electricity Applications—0
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability—0
A Dynamic-Adversarial Mining Approach to the Security of Machine Learning—0
Data Strategies for Fleetwide Predictive Maintenance—0
Correlation vs causation in Alzheimer's disease: an interpretability-driven study—0
Axiomatic Aggregations of Abductive Explanations—0
A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization—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
Data-Driven Transient Stability Assessment of Power Systems with a Novel GHM-Enhanced CatBoost Algorithm—0
Accurate and Robust Feature Importance Estimation under Distribution Shifts—0
An AI-driven framework for rapid and localized optimizations of urban open spaces—0
Automatic prediction of mortality in patients with mental illness using electronic health records—0
Enhanced Prediction of Ventilator-Associated Pneumonia in Patients with Traumatic Brain Injury Using Advanced Machine Learning Techniques—0
Analysis of Zero Day Attack Detection Using MLP and XAI—0
Analyze Additive and Interaction Effects via Collaborative Trees—0
Better Model Selection with a new Definition of Feature Importance—0
Analyzing Domestic Violence through Exploratory Data Analysis and Explainable Ensemble Learning Insights—0
Beyond Feature Importance: Feature Interactions in Predicting Post-Stroke Rigidity with Graph Explainable AI—0
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics—0
Beyond Single-Feature Importance with ICECREAM—0
Automatic Componentwise Boosting: An Interpretable AutoML System—0
Automated Speech Scoring System Under The Lens: Evaluating and interpreting the linguistic cues for language proficiency—0
A Multi-Head Attention Soft Random Forest for Interpretable Patient No-Show Prediction—0
Data-driven Prediction of Relevant Scenarios for Robust Combinatorial Optimization—0
Data Enrichment Opportunities for Distribution Grid Cable Networks using Variational Autoencoders—0
DDNet: Cartesian-polar Dual-domain Network for the Joint Optic Disc and Cup Segmentation—0
Crop yield probability density forecasting via quantile random forest and Epanechnikov Kernel function—0
A data-driven approach to the forecasting of ground-level ozone concentration—0
Cross-cultural Emotion Classification: the Effect of Emotional Intensity and Acoustic Features—0
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
Accurate and fast anomaly detection in industrial processes and IoT environments—0
CrossEAI: Using Explainable AI to generate better bounding boxes for Chest X-ray images—0
Coupling Machine Learning and Crop Modeling Improves Crop Yield Prediction in the US Corn Belt—0
COVID-19 diagnosis by routine blood tests using machine learning—0
A matching based clustering algorithm for categorical data—0
Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation—0
Crash Severity Risk Modeling Strategies under Data Imbalance—0
Data-driven advice for interpreting local and global model predictions in bioinformatics problems—0
Augmented Functional Random Forests: Classifier Construction and Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations—0
A machine learning approach to predict the structural and magnetic properties of Heusler alloy families—0
Local MDI+: Local Feature Importances for Tree-Based Models—0
Attention cannot be an Explanation—0
Regularizing Explanations in Bayesian Convolutional Neural Networks—0
AltFS: Agency-light Feature Selection with Large Language Models in Deep Recommender Systems—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