Ensemble Machine Learning Cookbook

coverpage

Title Page

Copyright and Credits

Ensemble Machine Learning Cookbook

About Packt

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Foreword

Contributors

About the authors

About the reviewers

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Preface

Who this book is for

What this book covers

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Download the example code files

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Conventions used

Sections

Getting ready

How to do it…

How it works…

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See also

Get in touch

Reviews

Get Closer to Your Data

Introduction

Data manipulation with Python

Getting ready

How to do it...

How it works...

There's more...

See also

Analyzing visualizing and treating missing values

How to do it...

How it works...

There's more...

See also

Exploratory data analysis

How to do it...

How it works...

There's more...

See also

Getting Started with Ensemble Machine Learning

Introduction to ensemble machine learning

Max-voting

Getting ready

How to do it...

How it works...

There's more...

Averaging

Getting ready

How to do it...

How it works...

Weighted averaging

Getting ready

How to do it...

How it works...

See also

Resampling Methods

Introduction to sampling

Getting ready

How to do it...

How it works...

There's more...

See also

k-fold and leave-one-out cross-validation

Getting ready

How to do it...

How it works...

There's more...

See also

Bootstrapping

Getting ready

How to do it...

How it works...

See also

Statistical and Machine Learning Algorithms

Technical requirements

Multiple linear regression

Getting ready

How to do it...

How it works...

There's more...

See also

Logistic regression

Getting ready

How to do it...

How it works...

See also

Naive Bayes

Getting ready

How to do it...

How it works...

There's more...

See also

Decision trees

Getting ready