classification modeling
✓Build binary and multiclass classification models using logistic regression, decision trees, and ensemble methods for categorical prediction and classification
Installation
SKILL.md
Classification modeling predicts categorical target values, assigning observations to discrete classes or categories based on input features.
Build binary and multiclass classification models using logistic regression, decision trees, and ensemble methods for categorical prediction and classification Source: aj-geddes/useful-ai-prompts.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill classification modeling Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Security certified for safe and reliable code One-click installation with simplified configuration Compatible with Claude Code, Cursor, and more
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill classification modeling- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-01
- Updated
- 2026-02-18
Quick answers
What is classification modeling?
Build binary and multiclass classification models using logistic regression, decision trees, and ensemble methods for categorical prediction and classification Source: aj-geddes/useful-ai-prompts.
How do I install classification modeling?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill classification modeling Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/aj-geddes/useful-ai-prompts
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-01