Tree-based Machine Learning Algorithms: Decision Trees, Random Forests, and Boosting
Tree-based Machine Learning Algorithms presents a focused exploration of decision trees, random forests, and boosting. With its attention to three important machine learning approaches, this book provides a useful starting point for students, practitioners, and readers seeking a concise introduction to tree-based methods.
About This Book
This book introduces tree-based machine learning algorithms through three central topics: decision trees, random forests, and boosting.
It offers a focused resource for readers studying machine learning and seeking an overview of these widely used methods.
The discussion centers on how these algorithmic approaches fit within the broader field of data-driven computing.
Suitable for learners, practitioners, and anyone interested in the foundations of tree-based models.
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