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Getting Started with Ensemble Machine Learning
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Getting Started with Ensemble Machine Learning
by Vijayalakshmi Natarajan, Dipayan Sarkar
Ensemble Machine Learning Cookbook
Title Page
Copyright and Credits
Ensemble Machine Learning Cookbook
About Packt
Why subscribe?
Packt.com
Foreword
Contributors
About the authors
About the reviewers
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Sections
Getting ready
How to do it…
How it works…
There's more…
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
How to do it...
How it works...
There's more...
See also
Support vector machines
Getting ready
How to do it...
How it works...
There's more...
See also
Bag the Models with Bagging
Introduction
Bootstrap aggregation
Getting ready
How to do it...
How it works...
See also
Ensemble meta-estimators
Bagging classifiers
How to do it...
How it works...
There's more...
See also
Bagging regressors
Getting ready
How to do it...
How it works...
See also
When in Doubt, Use Random Forests
Introduction to random forests
Implementing a random forest for predicting credit card defaults using scikit-learn
Getting ready
How to do it...
How it works...
There's more...
See also
Implementing random forest for predicting credit card defaults using H2O
Getting ready
How to do it...
How it works...
There's more...
See also
Boosting Model Performance with Boosting
Introduction to boosting
Implementing AdaBoost for disease risk prediction using scikit-learn
Getting ready
How to do it...
How it works...
There's more...
See also
Implementing a gradient boosting machine for disease risk prediction using scikit-learn
Getting ready
How to do it...
How it works...
There's more...
Implementing the extreme gradient boosting method for glass identification using XGBoost with scikit-learn 
Getting ready...
How to do it...
How it works...
There's more...
See also
Blend It with Stacking
Technical requirements
Understanding stacked generalization
Implementing stacked generalization by combining predictions
Getting ready...
How to do it... 
How it works...
There's more...
See also
Implementing stacked generalization for campaign outcome prediction using H2O
Getting ready...
How to do it...
How it works...
There's more...
See also
Homogeneous Ensembles Using Keras
Introduction
An ensemble of homogeneous models for energy prediction
Getting ready
How to do it...
How it works...
There's more...
See also
An ensemble of homogeneous models for handwritten digit classification
Getting ready
How to do it...
How it works...
Heterogeneous Ensemble Classifiers Using H2O
Introduction 
Predicting credit card defaulters using heterogeneous ensemble classifiers
Getting ready
How to do it...
How it works...
There's more...
See also
Heterogeneous Ensemble for Text Classification Using NLP
Introduction
Spam filtering using an ensemble of heterogeneous algorithms
Getting ready
How to do it...
How it works...
Sentiment analysis of movie reviews using an ensemble model
Getting ready
How to do it...
How it works...
There's more...
Homogenous Ensemble for Multiclass Classification Using Keras
Introduction
An ensemble of homogeneous models to classify fashion products
Getting ready
How to do it...
How it works...
See also
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Introduction to ensemble machine learning
Getting Started with Ensemble Machine Learning
In this
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hapter
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we'll cover the following recipes:
Max-voting
Averaging
Weighted averaging
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