Repository for developers that provides core functionality for the MLJ machine learning framework. MLJ is a Julia framework for combining and tuning machine learning models. This repository provides core functionality for MLJ.

Features

  • Completing the functionality for methods defined "minimally" in MLJ's light-weight model interface MLJModelInterface (/src/interface)
  • Definition of machines and their associated methods, such as fit! and predict/transform (src/machines)
  • MLJ's model composition interface, including learning networks, pipelines, stacks, target transforms (/src/composition)
  • Basic utilities for manipulating datasets and for synthesizing datasets (src/data)
  • Small interface for resampling strategies and implementations, including CV(), StratifiedCV and Holdout (src/resampling.jl)
  • Methods for performance evaluation, based on those resampling strategies (src/resampling.jl)

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