Welcome to Mapping Learning’s documentation!

Note

Mapping Learning (also called maplearn) makes use of machine learning easy (easier, at least). Initially designed for geographical data (cartography based on remote sensing), Maplearn also deals very well with classical data (ie tabular).

NB: information in french is available in maplearn’s wiki .

Maplearn is a free software and library, distributed under lGPL v3 license.

Written in Python, maplearn can be used whichever your operation system (Linux, Mac, Windows).

Features

• many algorithms to make predictions (classification, clustering or regression)
• look for best hyper-parameters to improve accuracy of your results
• generalize machine learning’s best practices (k-fold…)
• several preprocessing tasks available : reduction of dimensions…
• reads/writes several file formats (geographic or not)
• synthetizes results in a standardized report
• statiscal and more empirical advices will help novice users

Table of Contents

• Install
  • Installing
  • 2. Before installing
• Use
  • Mapping Learning’s GUI
  • Mapping Learning’s CLI
  • Output
• Source code
  • Modules
• Contribute
  • Documentation
  • Source code
  • Philosophy
  • Thanks

Indices and tables

• Index
• Module Index
• Search Page