Welcome to skfeaturellm’s documentation!

skfeaturellm is a Python library that leverages Large Language Models (LLMs) for automated feature engineering in machine learning pipelines. It is model-agnostic and works with any LLM available from LangChain (OpenAI, Anthropic, etc.).

Contents:

• Get Started
  • Installation
  • Key Concepts
  • Quickstart
• Installation
  • Installing Release Versions
  • Installing latest Development Version
  • Installing Full Developer Setup
• User Guide
  • Overview
  • Workflow
  • LLMFeatureEngineer Parameters
  • Dataset Statistics
  • Feature Transformation DSL
  • Production Pipeline with FeatureEngineeringTransformer
  • Iterative Feature Selection with fit_selective()
  • API Keys and Provider Configuration
• API Reference
  • Core Classes
  • Feature Engineering Transformer
  • LLM Interface
  • Schemas
  • Feature Evaluation
  • Reporting
  • Transformations
• Examples
  • Classification
  • Regression
  • Feature Evaluation and Selection
  • Production Pipeline
  • Saving and Loading
  • Notebook Tutorial

Indices and tables

• Index

• Module Index

• Search Page