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Interpreting Models
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Classroom Contents
A Taste of Random Decision Forests on Apache Spark
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- 1 Introduction
- 2 Feature Vectors in the Iris Data Set
- 3 Good Pet Data Set
- 4 Possible Decision Trees
- 5 Interpreting Models
- 6 Building a Decision Tree in MLlib
- 7 Evaluating a Decision Tree
- 8 Better Than Random Guessing?
- 9 Decisions Should Make Lower Impurity Subsets
- 10 Tuning Hyperparameters
- 11 How to Create a Crowd?
- 12 Trees See Subsets of Examples
- 13 Or Subsets of Features
- 14 Diversity of Opinion
- 15 Random Decision Forests
