Summary of Remarks on Loss Function Of Threshold Method For Ordinal Regression Problem, by Ryoya Yamasaki and Toshiyuki Tanaka
Remarks on Loss Function of Threshold Method for Ordinal Regression Problem
by Ryoya Yamasaki, Toshiyuki Tanaka
First submitted to arxiv on: 22 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper investigates threshold methods for ordinal regression problems, where data has a natural ordering. It analyzes how underlying data distribution and learning procedures affect classification performance, providing insights into when threshold methods may perform poorly or struggle with complex data. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The research explores the impact of data distribution and learning techniques on threshold methods for ordinal regression tasks. Results show that typical procedures can fail when target variable distributions are non-unimodal. Additionally, learned transformations tend to concentrate at specific points under certain loss functions, making it challenging to classify complex data. |
Keywords
» Artificial intelligence » Classification » Regression
