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Feature Importance

Papers

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Showing 451–500 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
Algorithm-Agnostic Interpretations for Clustering—0
Low-cost machine learning approach to the prediction of transition metal phosphor excited state properties—0
Sample-based Uncertainty Quantification with a Single Deterministic Neural Network—0
Examining Uniqueness and Permanence of the WAY EEG GAL dataset toward User Authentication—0
Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams—0
A Case Study on the Classification of Lost Circulation Events During Drilling using Machine Learning Techniques on an Imbalanced Large Dataset—0
Machine Learning Models Evaluation and Feature Importance Analysis on NPL Dataset—0
Learning to predict test effectiveness—0
An ensemble meta-estimator to predict source code testabilityCode0
Real-Time Robust Video Object Detection System Against Physical-World Adversarial Attacks—0
Unifying local and global model explanations by functional decomposition of low dimensional structuresCode0
Estimating Sunlight Using GNSS Signal Strength from Smartphone—0
EFI: A Toolbox for Feature Importance Fusion and Interpretation in PythonCode0
A machine learning approach to predict the structural and magnetic properties of Heusler alloy families—0
Bias Reducing Multitask Learning on Mental Health Prediction—0
Efficient Novelty Detection Methods for Early Warning of Potential Fatal DiseasesCode0
Parameter Averaging for Feature Ranking—0
MedML: Fusing Medical Knowledge and Machine Learning Models for Early Pediatric COVID-19 Hospitalization and Severity PredictionCode0
Neural Greedy Pursuit for Feature Selection—0
Explainable Deep Belief Network based Auto encoder using novel Extended Garson Algorithm—0
SHAP-XRT: The Shapley Value Meets Conditional Independence TestingCode0
The Impact of Feature Quantity on Recommendation Algorithm Performance: A Movielens-100K Case StudyCode0
A novel evaluation methodology for supervised Feature Ranking algorithmsCode0
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language ConversationsCode1
GLANCE: Global to Local Architecture-Neutral Concept-based ExplanationsCode0
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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