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Building Reliable Machine Learning Models with PyCaret: A Case Study on the LORIS Model

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Abstract

Introduction to PyCaret and Galaxy

Questions this will address

  • How can PyCaret be used in Galaxy to build and evaluate machine learning models?
  • What are the key features of PyCaret that simplify machine learning workflows?

Learning Objectives

  • Understand the capabilities of PyCaret for automating machine learning workflows.
  • Learn how to use PyCaret in Galaxy to build and compare machine learning models.
  • Apply PyCaret to the LORIS dataset to reproduce and evaluate the LORIS LLR6 model.

Licence: Creative Commons Attribution 4.0 International

Keywords: Statistics and machine learning

Target audience: Students

Resource type: slides

Version: 1

Status: Active

Learning objectives:

  • Understand the capabilities of PyCaret for automating machine learning workflows.
  • Learn how to use PyCaret in Galaxy to build and compare machine learning models.
  • Apply PyCaret to the LORIS dataset to reproduce and evaluate the LORIS LLR6 model.

Date modified: 2025-05-05

Date published: 2025-05-05

Authors: Jeremy Goecks, Junhao Qiu, Paulo Cilas Morais Lyra Junior

Scientific topics: Statistics and probability

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