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Feature Importance

Papers

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Showing 651–700 of 890 papers

TitleStatusHype
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input FeaturesCode0
Feature Selection for Imbalanced Data with Deep Sparse Autoencoders Ensemble—0
Trustworthy Disease Discovery: A Case Study in Alzheimer’s—0
Image Classifiers for Network Intrusions—0
Interpretable Data-driven Methods for Subgrid-scale Closure in LES for Transcritical LOX/GCH4 Combustion—0
A Comparative Approach to Explainable Artificial Intelligence Methods in Application to High-Dimensional Electronic Health Records: Examining the Usability of XAI—0
Understanding & Predicting User Lifetime with Machine Learning in an Anonymous Location-Based Social Network—0
Feature Importance Explanations for Temporal Black-Box ModelsCode1
An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery—0
Artificial Intelligence Enhanced Rapid and Efficient Diagnosis of Mycoplasma Pneumoniae Pneumonia in Children PatientsCode0
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs—0
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset—0
Feature Analyses and Modelling of Lithium-ion Batteries Manufacturing based on Random Forest Classification—0
Towards Better Explanations of Class Activation MappingCode0
WheaCha: A Method for Explaining the Predictions of Models of Code—0
Website fingerprinting on early QUIC traffic—0
Continual Deterioration Prediction for Hospitalized COVID-19 Patients—0
Benchmarking Perturbation-based Saliency Maps for Explaining Atari AgentsCode0
Robusta: Robust AutoML for Feature Selection via Reinforcement Learning—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
Modeling Household Online Shopping Demand in the U.S.: A Machine Learning Approach and Comparative Investigation between 2009 and 2017—0
Disentangled Self-Attentive Neural Networks for Click-Through Rate PredictionCode0
Explaining the Black-box Smoothly- A Counterfactual Approach—0
Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients—0
Facial Expression Recognition in the Wild via Deep Attentive Center LossCode1
Democratizing Evaluation of Deep Model Interpretability through Consensus—0
On the Discovery of Feature Importance Distribution: An Overlooked AreaCode0
Prediction of Enzyme Specificity using Protein Graph Convolutional Neural Networks—0
Elastic Net based Feature Ranking and SelectionCode0
GANterfactual - Counterfactual Explanations for Medical Non-Experts using Generative Adversarial LearningCode1
Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift AlgorithmCode0
Using Spatio-temporal Deep Learning for Forecasting Demand and Supply-demand Gap in Ride-hailing System with Anonymised Spatial Adjacency Information—0
E2E-FS: An End-to-End Feature Selection Method for Neural NetworksCode1
Evaluating Explainable Methods for Predictive Process Analytics: A Functionally-Grounded ApproachCode0
Shapley values for cluster importance: How clusters of the training data affect a prediction—0
AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous SensorsCode0
Representaciones del aprendizaje reutilizando los gradientes de la retropropagacion—0
Hate and Toxic Speech Detection in the Context of Covid-19 Pandemic using XAI: Ongoing Applied Research—0
A Linguistic Perspective on Reference: Choosing a Feature Set for Generating Referring Expressions in Context—0
RANCC: Rationalizing Neural Networks via Concept ClusteringCode0
Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for AutoencodersCode1
What went wrong and when?\\ Instance-wise feature importance for time-series black-box models—0
TimeSHAP: Explaining Recurrent Models through Sequence PerturbationsCode1
FIST: A Feature-Importance Sampling and Tree-Based Method for Automatic Design Flow Parameter Tuning—0
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same EndCode2
Multi-View Adaptive Fusion Network for 3D Object DetectionCode1
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetCode1
AutoAtlas: Neural Network for 3D Unsupervised Partitioning and Representation LearningCode0
Shapley Flow: A Graph-based Approach to Interpreting Model PredictionsCode1
Bayesian Importance of Features (BIF)Code0
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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