Welcome to Ontolearn’s documentation!

Ontolearn is an open-source software library for explainable structured machine learning in Python.

Contents:

• About Ontolearn
• Installation
  • Installation via pip
  • Installation From Source
  • Download External Files
  • Building (sdist and bdist_wheel)
  • Simple Linting
• Examples
  • Ex. 1: Learning Over a Local Ontology
  • Ex. 2: Learning Over a Triplestore Ontology
  • Ex. 3: CMD Friendly Execution
• Knowledge Bases
  • Knowledge Base vs Ontology
  • Create an Instance of KnowledgeBase
  • Ignore Concepts
  • Accessing Individuals
  • Sampling the Knowledge Base
  • TripleSore Knowledge Base
  • Loading and Launching a Triplestore
  • Obtaining axioms
• Evaluate a class expression
  • Construct a learning problem
  • Construct a concept
  • Evaluation and results
• Concept Learning
  • Expressiveness
  • Prerequisites
  • Configuring Input Parameters
  • Configure the Learning Problem
  • Configuring & Executing a Concept Learner
• Further Resources
  • Citing
  • More Inside the Project
  • Contribution
  • Questions
  • Code Coverage
• ontolearn
  • Submodules
  • Attributes
  • Package Contents