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SPIN Processed News Frame: The Fog

Mutual information and sensitivity analysis for feature selection in customer targeting: a comparative study

A comparative study evaluates mutual information and data-based sensitivity analysis for feature selection in bank telemarketing, finding mutual information selects 13 features with slightly better performance at high false positive ratios, while sensitivity analysis selects 9 features and achieves lower false positives.

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arXiv Machine Learning

Aug 24, 2026

SPIN Processed News Frame: The Hype

High-Order Markov Blanket Discovery via a k-Order Relaxation of the Faithfulness Assumption

A new research paper introduces a k-order relaxation of the faithfulness assumption to improve Markov blanket discovery in graphical models, addressing known failure modes from higher-order dependencies and finite-sample artifacts.

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arXiv Machine Learning

Jul 30, 2026

SPIN Processed News Frame: The Cushion

Conditional Inference Trees and Forests for Feature Selection

A new arXiv preprint evaluates Conditional Inference Forests (CIF) as a feature-ranking method, finding it ranks 3rd–4th among dozens of methods on real-world classification and regression benchmarks while highlighting substantial runtime trade-offs and sampling limitations.

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arXiv Machine Learning

Published Jul 3, 2026 · Analyzed Jul 6, 2026