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LinkedIn Learning

Machine Learning and AI: Advanced Decision Trees with SPSS

via LinkedIn Learning

Overview

Work toward a mastery of machine learning by exploring advanced decision tree algorithm concepts. Learn about the QUEST and C5.0 algorithms and a few advanced topics.

Syllabus

Introduction
  • Welcome
  • What you should know
  • Using the exercise files
1. Understanding QUEST
  • Overview
  • How QUEST handles nominal variables
  • How QUEST handles ordinal and continuous variables
  • How QUEST handles missing data
  • Pruning in QUEST
  • Stopping rules in QUEST
2. Understanding C5.0
  • ID3 and C4.5
  • Winnowing attributes
  • Rule sets
  • Understanding information gain
  • Pruning in C5.0
  • How C5.0 handles missing data
3. Advanced Topics
  • Ensembles
  • What is bagging?
  • Using bagging for feature selection
  • Random forests
  • What is boosting?
  • Costs and priors
Conclusion
  • Next steps

Taught by

Keith McCormick

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