Ensemble machine learning cookbook : over 35 practical recipes to explore ensemble machine learning techniques using Python [E-Book] / Dipayan Sarkar, Vijayalakshmi Natarajan.
Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different...
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Full text |
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Personal Name(s): | Sarkar, Dipayan, author |
Natarajan, Vijayalakshmi, author | |
Edition: |
1st edition |
Imprint: |
[Birmingham] :
Packt Publishing,
2019
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Physical Description: |
327 pages (online resource) |
Note: |
englisch |
ISBN: |
9781789132502 9781789136609 |
Subject (ZB): | |
Subject (LOC): | |
Classification: |
- Ensemble machine learning cookbook: over 35 practical recipes to explore ensemble machine learning techniques using Python
- Foreword
- Contributors
- Preface
- Table of Contents
- Chapter 1: Get Closer to Your Data
- Chapter 2: Getting Started with Ensemble Machine Learning
- Chapter 3: Resampling Methods
- Chapter 4: Statistical and Machine Learning Algorithms
- Chapter 5: Bag the Models with Bagging
- Chapter 6: When in Doubt, Use Random Forests
- Chapter 7: Boosting Model Performance with Boosting
- Chapter 8: Blend It with Stacking
- Chapter 9: Homogeneous Ensembles Using Keras
- Chapter 10: Heterogeneous Ensemble Classifiers Using H2O
- Chapter 11: Heterogeneous Ensemble for Text Classification Using NLP
- Chapter 12: Homogenous Ensemble for Multiclass Classification Using Keras
- Other Books You May Enjoy
- Index.