August 2024
Intermediate to advanced
374 pages
8h 44m
English
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Making Decisions
Perhaps the most popular non-deep-learning algorithms in use today are decision trees and their ensemble variants, such as gradient boosting.
Decision trees behave exactly as they sound: they construct nested trees based on input features. Decision trees construct a hierarchical decision flow that partitions input features into one of a desired number of classes. For example, imagine you were trying to create a model to predict whether or not a patient was at risk of heart disease. A decision tree would construct a tree that analyzes data in an interpretable way. Does the patient smoke? Does the patient have high blood pressure? Is the patient physically active?
Decision trees are incredibly popular because they are interpretable, ...
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