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Test Driven Machine Learning

Book Image

Test Driven Machine Learning

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Test Driven Machine Learning
Nov, 2015 | 190 pages
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Table of Contents (16 chapters)
Test-Driven Machine Learning
Test-Driven Machine Learning
Credits
Credits
About the Author
About the Author
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
Introducing Test-Driven Machine Learning
Introducing Test-Driven Machine Learning
Test-driven development
The TDD cycle
Behavior-driven development
Our first test
TDD applied to machine learning
Dealing with randomness
Different approaches to validating the improved models
Quantifying the classification models
Summary
2
Perceptively Testing a Perceptron
Perceptively Testing a Perceptron
Getting started
Summary
3
Exploring the Unknown with Multi-armed Bandits
Exploring the Unknown with Multi-armed Bandits
Understanding a bandit
Testing with simulation
Starting from scratch
Simulating real world situations
A randomized probability matching algorithm
A bootstrapping bandit
The problem with straight bootstrapping
Multi-armed armed bandit throw down
Summary
4
Predicting Values with Regression
Predicting Values with Regression
Refresher on advanced regression
Generating our own data
Building the foundations of our model
Cross-validating our model
Generating data
Summary
5
Making Decisions Black and White with Logistic Regression
Making Decisions Black and White with Logistic Regression
Generating logistic data
Measuring model accuracy
Generating a more complex example
Test driving our model
Summary
6
You're So Naïve, Bayes
You're So Naïve, Bayes
Gaussian classification by hand
Beginning the development
Summary
7
Optimizing by Choosing a New Algorithm
Optimizing by Choosing a New Algorithm
Upgrading the classifier
Applying our classifier
Upgrading to Random Forest
Summary
8
Exploring scikit-learn Test First
Exploring scikit-learn Test First
Test-driven design
Planning our journey
Getting choosey
Developing testable documentation
Summary
9
Bringing It All Together
Bringing It All Together
Starting at the highest level
The real world
What we've accomplished
Summary
Index
Index

Chapter 3. Exploring the Unknown with Multi-armed Bandits

We'll start this chapter by building a simplistic algorithm and measuring its quality. Next, we'll build a much more intelligent algorithm. We will also build some tests to measure the quality improvement that we will achieve, specifically, a multi-armed bandit algorithm.

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