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Feature Importance

Papers

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Showing 651–700 of 890 papers

TitleStatusHype
Automatic Componentwise Boosting: An Interpretable AutoML System—0
Feature Importance in Gradient Boosting Trees with Cross-Validation Feature Selection—0
Model Explanations via the Axiomatic Causal LensCode0
Optimizing model-agnostic Random Subspace ensemblesCode0
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process—0
Inferring feature importance with uncertainties in high-dimensional dataCode0
Feature Importance in a Deep Learning Climate Emulator—0
Data-driven advice for interpreting local and global model predictions in bioinformatics problems—0
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition—0
Improved Feature Importance Computations for Tree Models: Shapley vs. Banzhaf—0
Locally Interpretable One-Class Anomaly Detection for Credit Card Fraud DetectionCode0
Explainable Debugger for Black-box Machine Learning ModelsCode0
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images—0
Feature importance recap and stacking models for forex price prediction—0
Feature Importance Guided Attack: A Model Agnostic Adversarial Attack—0
Interpreting Criminal Charge Prediction and Its Algorithmic Bias via Quantum-Inspired Complex Valued Networks—0
Machine learning to tame divergent density functional approximations: a new path to consensus materials design principles—0
Neural network interpretability for forecasting of aggregated renewable generationCode0
Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT)Code0
FairCanary: Rapid Continuous Explainable Fairness—0
Predicting Knowledge Gain during Web Search based on Multimedia Resource Consumption—0
Evaluating Local Explanations using White-box Models—0
A Methodology for Exploring Deep Convolutional Features in Relation to Hand-Crafted Features with an Application to Music Audio ModelingCode0
Evaluating the Correctness of Explainable AI Algorithms for Classification—0
Algorithm-Agnostic Explainability for Unsupervised ClusteringCode0
Is Gender "In-the-Wild" Inference Really a Solved Problem?Code0
Learning Bermudans—0
Regularizing Explanations in Bayesian Convolutional Neural Networks—0
Twin Systems for DeepCBR: A Menagerie of Deep Learning and Case-Based Reasoning Pairings for Explanation and Data Augmentation—0
Towards Rigorous Interpretations: a Formalisation of Feature AttributionCode0
LCS-DIVE: An Automated Rule-based Machine Learning Visualization Pipeline for Characterizing Complex Associations in Classification—0
Facilitating Machine Learning Model Comparison and Explanation Through A Radial Visualisation—0
LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer InformationCode0
Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML—0
Transforming Feature Space to Interpret Machine Learning ModelsCode0
Hollow-tree Super: a directional and scalable approach for feature importance in boosted tree models—0
Online Feature Screening for Data Streams with Concept Drift—0
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
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
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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