README.md

metadata

language:
  - en
task_categories:
  - text-classification
task_ids:
  - multi-label-classification
pretty_name: Scikit-learn GitHub Issues (Multilabel)
license: apache-2.0

🧩 Scikit-learn GitHub Issues – Multilabel Dataset

This dataset contains GitHub issues from the scikit-learn repository, prepared for multilabel NLP tasks such as issue tagging, automated triage, and semantic search.

Each row corresponds to one issue-comment context, making the dataset suitable for real-world developer tooling.

---

📌 Motivation

GitHub issues are a critical signal in open-source projects:

• Bug tracking
• Feature requests
• Documentation improvements
• Module-specific discussions

This dataset enables:

• Multilabel text classification
• Label recommendation systems
• Semantic search over issues
• Downstream LLM & RAG pipelines

---

📦 Dataset Construction

Source

• Repository: scikit-learn/scikit-learn
• Collected using the GitHub REST API

Included

• Open & closed issues
• Issue title + body
• All comments
• Original GitHub labels

Excluded

• Pull requests

---

🔄 Preprocessing Pipeline

1. Retrieved issues up to API safety limits
2. Removed pull requests
3. Downloaded all issue comments
4. Exploded issues by comments
5. Constructed a unified text field:
   • title
   • body
   • comments
6. Extracted label names into a multilabel format

---

📊 Dataset Overview

• Samples: ~12,500
• Labels per sample: 1–6
• Unique labels: ~20+
• Language: English

Example labels:

• Bug
• Documentation
• New Feature
• module:linear_model
• Build / CI
• Needs Triage

---

🧱 Dataset Columns

Column	Description
html_url	GitHub issue URL
labels	List of labels (multilabel target)
text	Issue title + body + comments
issue_number	Original GitHub issue number

Column types are inferred automatically from the dataset files.

---

🚀 Intended Use

• Multilabel classification
• Issue triage automation
• Semantic search
• Developer-facing ML tools

---

⚠️ Limitations

• Natural class imbalance
• Domain-specific to scikit-learn
• Label taxonomy evolves over time

---

👤 Author

Talip7
Focused on applied NLP, real-world datasets, and production ML pipelines.