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Machine Learning with R

You're reading from   Machine Learning with R R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required ‚Äì this book will take you methodically through every stage of applying machine learning.

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Product type Paperback
Published in Oct 2013
Publisher Packt
ISBN-13 9781782162148
Length 396 pages
Edition 1st Edition
Languages
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Author (1):
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Brett Lantz Brett Lantz
Author Profile Icon Brett Lantz
Brett Lantz
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Table of Contents (19) Chapters Close

Machine Learning with R
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Introducing Machine Learning FREE CHAPTER 2. Managing and Understanding Data 3. Lazy Learning – Classification Using Nearest Neighbors 4. Probabilistic Learning – Classification Using Naive Bayes 5. Divide and Conquer – Classification Using Decision Trees and Rules 6. Forecasting Numeric Data – Regression Methods 7. Black Box Methods – Neural Networks and Support Vector Machines 8. Finding Patterns – Market Basket Analysis Using Association Rules 9. Finding Groups of Data – Clustering with k-means 10. Evaluating Model Performance 11. Improving Model Performance 12. Specialized Machine Learning Topics Index

Chapter 10. Evaluating Model Performance

Many years ago, when only the wealthy could afford access to education, tests and examinations were not used to evaluate the students. Instead, they were used to judge the teachers—parents wanted to know whether their children were learning enough to justify the instructors' wages. Obviously, this practice has changed over the years. Now, such evaluations are used to distinguish between high and low-achieving students, filtering them into careers and further educational opportunities.

Given the significance of this process, a great deal of effort is invested in developing accurate student assessments. A fair assessment will have a large number of questions to cover a wide breadth of topics and reward true knowledge over lucky guesses. The assessment should also include some questions requiring the student to think about a problem he or she has never faced before. Correct responses would indicate that the student can apply the knowledge more generally...

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