Multiple Linear Regression Coefficients for Adversarial Points from DGCNN

9.5 KB Excel file containing regression coefficients from analyses of points with high adversarial scores derived from a Dynamic Graph Convolutional Neural Network (DGCNN). The dataset, authored by Hanieh Naderi and last updated on April 21, 2026, likely contains significant coefficients shown with three-decimal precision and insignificant ones shown as zero.

Use Cases

• Analyzing the relationship between adversarial scores and other variables based on the regression coefficients.
• Validating or comparing regression models for adversarial point analysis based on the coefficient significance and precision.
• Investigating feature importance in adversarial attacks on graph neural networks based on the coefficient magnitudes.

Strengths

• Coefficients are reported with a precision of three decimal points, which may allow for detailed analysis.
• Dataset is openly licensed under CC-BY-4.0, permitting reuse and redistribution.
• File size is 9.5 KB, making it quick to download and inspect.

Limitations

• Row count and column definitions are unknown, which limits suitability assessment.
• Description metadata is limited; actual data quality and variable semantics require manual inspection after download.

Provenance

Source

Hanieh Naderi via figshare

Collection Method

Derived from analyses of points with high adversarial scores from a DGCNN model.

Time Range

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Freshness

Last updated 2026-04-21 17:38:29; freshness should be verified.

Geography

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