Sign-In
Cart
Tree-Based Methods for Statistical Learning in R
Hardcover
Series: Chapman & Hall/CRC Data Science
Business GeneralProbability & Statistics
ISBN13: 9780367532468
Publisher: Crc Pr Inc
Published: Jun 23 2022
Pages: 404
Weight: 1.64
Height: 0.94 Width: 6.14 Depth: 9.21
Language: English
Tree-based Methods for Statistical Learning in R provides a thorough introduction to both individual decision tree algorithms (Part I) and ensembles thereof (Part II). Part I of the book brings several different tree algorithms into focus, both conventional and contemporary. Building a strong foundation for how individual decision trees work will help readers better understand tree-based ensembles at a deeper level, which lie at the cutting edge of modern statistical and machine learning methodology.
The book follows up most ideas and mathematical concepts with code-based examples in the R statistical language; with an emphasis on using as few external packages as possible. For example, users will be exposed to writing their own random forest and gradient tree boosting functions using simple for loops and basic tree fitting software (like rpart and party/partykit), and more. The core chapters also end with a detailed section on relevant software in both R and other opensource alternatives (e.g., Python, Spark, and Julia), and example usage on real data sets. While the book mostly uses R, it is meant to be equally accessible and useful to non-R programmers.
Consumers of this book will have gained a solid foundation (and appreciation) for tree-based methods and how they can be used to solve practical problems and challenges data scientists often face in applied work.
Features:
-
Thorough coverage, from the ground up, of tree-based methods (e.g., CART, conditional inference trees, bagging, boosting, and random forests).
- A companion website containing additional supplementary material and the code to reproduce every example and figure in the book.
- A companion R package, called treemisc, which contains several data sets and functions used throughout the book (e.g., there's an implementation of gradient tree boosting with LAD loss that shows how to perform the line search step by updating the terminal node estimates of a fitted rpart tree).
- Interesting examples that are of practical use; for example, how to construct partial dependence plots from a fitted model in Spark MLlib (using only Spark operations), or post-processing tree ensembles via the LASSO to reduce the number of trees while maintaining, or even improving performance.
Also from
Greenwell, Brandon M.
Also in
Probability & Statistics
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Grolemund, Garrett
Wickham, Hadley
Paperback
AP Statistics Premium, 2027: 9 Practice Tests + Comprehensive Review + Online Practice
Sternstein, Martin, PH. D.
Paperback
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Cetinkaya-Rundel, Mine
Wickham, Hadley
Grolemund, Garrett
Paperback
Graph Paper Composition Notebook: Quad Ruled 5x5, Grid Paper for Students in Math and Science
Wizo, Math
Paperback
Forecasting: Principles and Practice, the Pythonic Way
Hyndman, Rob J.
Athanasopoulos, George
Paperback
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
Spiegelhalter, David
Paperback
Stat 208 Statistical Thinking: A Book for Stat 208 at Virginia Commonwealth University
Street IV, W. Scott
Durfee, Becky
Paperback
Mastering Claude AI: Practical Journey from First Prompts to Pro with Claude AI
Dickey, Ryan
Paperback
An Introduction to Statistical Learning: With Applications in R
Hastie, Trevor
James, Gareth
Witten, Daniela
Paperback
Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries
Frost, Jim
Paperback
Ai-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Bruce, Peter
Bruce, Andrew
Gedeck, Peter
Paperback
Scale: The Universal Laws of Life, Growth, and Death in Organisms, Cities, and Companies
West, Geoffrey
Paperback
How the World Really Works: The Science Behind How We Got Here and Where We're Going
Smil, Vaclav
Paperback
The Art of Uncertainty: How to Navigate Chance, Ignorance, Risk and Luck
Spiegelhalter, David
Hardcover
The Random Universe: How Models and Probability Help Us Make Sense of the Cosmos
Jaffe, Andrew H.
Hardcover
Schaum's Outline of Probability and Statistics, 4th Edition: 897 Solved Problems + 20 Videos
Spiegel, Murray R.
Schiller, John J.
Srinivasan, R. Alu
Paperback
Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results
Hatcher, Larry
Paperback
The Only Math Book You'll Ever Need, Revised Edition: Hundreds of Easy Solutions and Shortcuts for Mastering Everyday Numbers
Heller, Barbara R.
Kogelman, Stanley
Paperback
Schaum's Outline of Probability, Random Variables, and Random Processes, Fourth Edition
Hsu, Hwei P.
Paperback
Mathletics: How Gamblers, Managers, and Fans Use Mathematics in Sports, Second Edition
Winston, Wayne L.
Nestler, Scott
Pelechrinis, Konstantinos
Paperback
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Yu, James
Cheng, Ran
Lee, Peter
Hardcover
Building Large Language Models from Scratch: Design, Train, and Deploy Llms with Pytorch
Grigorov, Dilyan
Paperback
The End of Average: Unlocking Our Potential by Embracing What Makes Us Different
Rose, Todd
Paperback
How the World Really Works: The Science Behind How We Got Here and Where We're Going
Smil, Vaclav
Hardcover
Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis
Harrell Jr, Frank E.
Paperback
Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists
Best, Joel
Hardcover
SQL Server 2025 Unveiled: The Ai-Ready Enterprise Database with Microsoft Fabric Integration
Ward, Bob
Paperback
Challenging Mathematical Problems with Elementary Solutions, Vol. I: Volume 1
Yaglom, A. M.
Yaglom, I. M.
Paperback
Databricks Data Intelligence Platform: Unlocking the Genai Revolution
Gupta, Nikhil
Yip, Jason
Paperback
System Design with AI Interview Guide: Designing Scalable, Agentic, and Defensible Systems
Bhardwaj, Rohit
Paperback
Quantum Computing and Quantum Machine Learning for Engineers and Developers
Van Griensven Thé, Jesse
Rosas-Bustos, Jose
Fraser, Roydon Andrew
Hardcover
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
Domingos, Pedro
Paperback
Making ChatGPT Work for You: Getting the Most Out of Generative AI as a Non-Techie
Evelyn, Lydia
Paperback
Large Language Models: A Deep Dive: Bridging Theory and Practice
Keenan, Kevin
Somers, Garrett
Kamath, Uday
Hardcover
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Downey, Allen B.
Paperback
Probably the Best Book on Statistics Ever Written: How to Beat the Odds and Make Better Decisions
Shapira, Haim
Hardcover
The Theory That Would Not Die: How Bayes' Rule Cracked the Enigma Code, Hunted Down Russian Submarines, and Emerged Triumphant from Two Centuries of C
McGrayne, Sharon Bertsch
Paperback
Scorecasting: The Hidden Influences Behind How Sports Are Played and Games Are Won
Moskowitz, Tobias
Wertheim, L. Jon
Paperback
Guide to Methods for Students of Political Science: Property, Proof, and Dispute in Catalonia Around the Year 1000
Van Evera, Stephen
Paperback
Time Series Analysis and Its Applications: With R Examples
Shumway, Robert H.
Stoffer, David S.
Hardcover
An Introduction to Statistical Learning: With Applications in Python
Hastie, Trevor
James, Gareth
Witten, Daniela
Hardcover
AI for Robotics: Toward Embodied and General Intelligence in the Physical World
Gopalakrishnan, Keerthana
Imran, Alishba
Paperback
Probably Overthinking It: How to Use Data to Answer Questions, Avoid Statistical Traps, and Make Better Decisions
Downey, Allen B.
Hardcover
Machine Learning Q and AI: 30 Essential Questions and Answers on Machine Learning and AI
Raschka, Sebastian
Paperback
A Modern Introduction to Probability and Statistics: Understanding Why and How
Lopuhaä, H. P.
Dekking, F. M.
Kraaikamp, C.
Hardcover
Mathematical Modeling and Computation in Finance: With Exercises and Python and MATLAB Computer Codes
Grzelak, Lech A.
Oosterlee, Cornelis W.
Paperback
Learning Statistics with Jamovi: A Tutorial for Beginners in Statistical Analysis
Navarro, Danielle
Foxcroft, David
Paperback
Modern Time Series Forecasting with Python - Second Edition: Industry-ready machine learning and deep learning time series analysis with PyTorch and p
Joseph, Manu
Tackes, Jeffrey
Paperback
Mathematical Foundations of Quantum Computing: A Scaffolding Approach
Yu, James
Cheng, Ran
Lee, Peter
Paperback
Challenging Mathematical Problems with Elementary Solutions, Vol. II: Volume 2
Yaglom, A. M.
Yaglom, I. M.
Paperback
Observability for Large Language Models: Site Reliability and Chaos Engineering for AI at Scale
Sharma, Ankush
Paperback
Introduction to Statistics: An Intuitive Guide for Analyzing Data and Unlocking Discoveries
Frost, Jim
Hardcover
Prompt Engineering for Everyone: A Self-Taught, Human-Centered Approach to AI Programming
Tavakoli, Hamid
Paperback
The Design Inference: Eliminating Chance through Small Probabilities
Dembski, William A.
Ewert, Winston
Hardcover
High-Dimensional Probability: An Introduction with Applications in Data Science
Vershynin, Roman
Hardcover
Discrete Nonlinear Schrodinger Equation: Beyond Complete Integrability
Pankov, Alexander
Zhang, Guoping
Hardcover
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
Hastie, Trevor
Tibshirani, Robert
Friedman, Jerome
Hardcover
ACCUPLACER Math Prep: ACCUPLACER Math Test Study Guide with Two Practice Tests [Includes Detailed Answer Explanations]
Tpb Publishing
Paperback
Telling Time Workbook: Practice Reading and Draw the Hand on the Clocks One Hour Half Hour 15 5 1 Minutes
Winny, Renzo
Paperback
Large Language Model Recipes: A Hands-On Guide to Fine-Tuning, Optimization, Deployment, and Real-World Applications
Kaata, Sashi Kiran
Bolla, Bharath Kumar
Subbaiah, Kalpa
Paperback
Unlocking Dbt: Design and Deploy Transformations in Your Cloud Data Warehouse
Cyr, Cameron
Dorsey, Dustin
Paperback
Bayesian Analysis with Python - Third Edition: A practical guide to probabilistic modeling
Martin, Osvaldo
Paperback
The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements and Statistics
Mitchell, Andy
Griffin, Lauren Scott
Paperback
Databricks Data Intelligence Platform: Powering the Agentic Era
Yip, Jason
Gupta, Nikhil
Wojtyczka, Marcin
Paperback
Practical Generative Ai: From Concept to Deployment: Building and Deploying Ethical AI-Powered Solutions
Singh, Pramod
McKeone, James
Paperback
R in Action, Third Edition: Data Analysis and Graphics with R and Tidyverse
Kabacoff, Robert I.
Paperback
Building AI Systems with Python: Practical Machine Learning and Agentic Workflows with Python and Pytorch
Hander, Martin
Paperback
Building Generative AI Agents: Using Langgraph, Autogen, and Crewai
Taulli, Tom
Deshmukh, Gaurav
Paperback
Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin
Adam, John a.
Weinstein, Lawrence
Paperback