XGBoost for regression predictive modeling and time series analysis : learn how to build, evaluate, and deploy predictive models with expert guidance

Author/Creator:

Deka, Partha Pritam, author

Publication/Creation:

Birmingham, UK : Packt Publishing Ltd., 2024

Format:

Book

Edition:

1st edition.

More Details

Additional/Related Title Information

Full Title:

XGBoost for regression predictive modeling and time series analysis : learn how to build, evaluate, and deploy predictive models with expert guidance / Partha Pritam Deka, Joyce Weiner

Related Names

Additional Author/Creators:

Weiner, Joyce, author

Subjects/Genre

Genre:

Electronic books

Subjects:

Machine learning
Regression analysis--Data processing
Time-series analysis--Data processing
Python (Computer program language)

Description/Summary

Summary:

XGBoost offers a powerful solution for regression and time series analysis, enabling you to build accurate and efficient predictive models. In this book, the authors draw on their combined experience of 40+ years in the semiconductor industry to help you harness the full potential of XGBoost, from understanding its core concepts to implementing real-world applications. As you progress, you'll get to grips with the XGBoost algorithm, including its mathematical underpinnings and its advantages over other ensemble methods. You'll learn when to choose XGBoost over other predictive modeling techniques, and get hands-on guidance on implementing XGBoost using both the Python API and scikit-learn API. You'll also get to grips with essential techniques for time series data, including feature engineering, handling lag features, encoding techniques, and evaluating model performance. A unique aspect of this book is the chapter on model interpretability, where you'll use tools such as SHAP, LIME, ELI5, and Partial Dependence Plots (PDP) to understand your XGBoost models. Throughout the book, you'll work through several hands-on exercises and real-world datasets. By the end of this book, you'll not only be building accurate models but will also be able to deploy and maintain them effectively, ensuring your solutions deliver real-world impact.

Language:

English

Physical Type/Description:

1 online resource

General Note:

Includes index.

Local Note:

Available to current Emory faculty, students and staff.

Additional Identifiers

Catalog ID (MMSID):

9938055597602486

ISBN:

9781805129608
1805129600

OCLC Number:

1472148234