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Feature Importance

Papers

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Showing 451–475 of 890 papers

TitleStatusHype
Comparing Explanation Methods for Traditional Machine Learning Models Part 2: Quantifying Model Explainability Faithfulness and Improvements with Dimensionality Reduction—0
Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection—0
Comparing Explanation Methods for Traditional Machine Learning Models Part 1: An Overview of Current Methods and Quantifying Their Disagreement—0
Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approach—0
Estimating oil recovery factor using machine learning: Applications of XGBoost classification—0
Which is the best model for my data?—0
Cards Against AI: Predicting Humor in a Fill-in-the-blank Party GameCode1
Neural Eigenfunctions Are Structured Representation LearnersCode1
Greedy Modality Selection via Approximate Submodular Maximization—0
Abstract Interpretation-Based Feature Importance for SVMs—0
Similarity of Neural Architectures using Adversarial Attack Transferability—0
Positive-Unlabeled Learning using Random Forests via Recursive Greedy Risk MinimizationCode1
Linear Video Transformer with Feature Fixation—0
TractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography—0
Saliency Map Verbalization: Comparing Feature Importance Representations from Model-free and Instruction-based MethodsCode0
A Detailed Study of Interpretability of Deep Neural Network based Top TaggersCode0
Interpreting County Level COVID-19 Infection and Feature Sensitivity using Deep Learning Time Series ModelsCode0
Conditional Feature Importance for Mixed DataCode0
Feature Importance for Time Series Data: Improving KernelSHAP—0
Ensembling improves stability and power of feature selection for deep learning models—0
To the Most Gracious Highness, from Your Humble Servant: Analysing Swedish 18th Century Petitions Using Text Classification—0
Sequential Attention for Feature SelectionCode0
Variance Tolerance Factors For Interpreting ALL Neural NetworksCode0
Concept Activation Regions: A Generalized Framework For Concept-Based ExplanationsCode1
An Attention Matrix for Every Decision: Faithfulness-based Arbitration Among Multiple Attention-Based Interpretations of Transformers in Text Classification—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