Elastic Net Regularization Paths for All Generalized Linear Models

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Physical Sciences › Mathematics › Statistics and Probability

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Identified Weaknesses

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Paper Summary

Paperzilla title

glmnet: Now Regularizes All the GLMs (But Mostly a Software Manual)

This paper details the implementation of elastic net regularization for all generalized linear models (GLMs), Cox models with extended data types, and a simplified relaxed lasso within the glmnet R package. It also covers utility functions for evaluating fitted model performance.

Possible Conflicts of Interest

None identified

Identified Weaknesses

Lack of Novel Research Contribution

The paper primarily focuses on software documentation and implementation details rather than presenting novel research findings.

Insufficient Evaluation

The paper lacks rigorous evaluation or comparison with existing methods, making it difficult to assess the impact of the implemented extensions.

Resemblance to Technical Documentation

The paper's focus on software details makes it read more like a technical report or manual rather than a scientific paper.

Rating Explanation

The paper provides a comprehensive overview of the glmnet package's extended functionalities for elastic net regularization. However, it lacks novel research contributions or substantial evaluation, making it more of a software documentation than a groundbreaking scientific paper. Therefore, a rating of 3 is appropriate.

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Topic Hierarchy

Domain:

Physical Sciences

Field:

Mathematics

Subfield:

Statistics and Probability

File Information

Original Title:

Elastic Net Regularization Paths for All Generalized Linear Models

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