Machine Learning and AI: Advanced Decision Trees with SPSS
Machine Learning and AI: Advanced Decision Trees with SPSS
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 23m | 193 MB
Instructor: Keith McCormick
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 23m | 193 MB
Instructor: Keith McCormick
If you're working towards an understanding of machine learning, it's important to know how to work with decision trees. In this course, explore advanced concepts and details of decision tree algorithms. Learn about the QUEST algorithm and how it handles nominal variables, ordinal and continuous variables, and missing data. Explore the C5.0 algorithm and review some of its key features such as global pruning and winnowing. Plus, dive into a few advanced topics that apply to all decision trees, such as boosting and bagging.
Learning objectives
- Understanding QUEST functions and applications
- C5.0 concepts and practical applications
- Understanding information gain
- Random forests
- Boosting and bagging
- Costs and priors
Machine Learning and AI: Advanced Decision Trees with SPSS
