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Applied Unsupervised Learning with R

You're reading from Applied Unsupervised Learning with R

Product type Book

Published in Mar 2019

Publisher

ISBN-13 9781789956399

Pages 320 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Authors (2):

Alok Malik

Bradford Tuckfield

View More author details

Table of Contents (9) Chapters

Applied Unsupervised Learning with R

Preface

1. Introduction to Clustering Methods

2. Advanced Clustering Methods

3. Probability Distributions

4. Dimension Reduction

5. Data Comparison Methods

6. Anomaly Detection

Appendix

Kernel Density

To conclude the chapter, we will discuss using kernel density estimates to perform outlier detection on a set of blood samples. Kernel density estimation provides a natural way to test whether a particular set of blood results are anomalous, even without having specialized knowledge of the particular blood test being used or even of medicine in general.

Suppose that you are working at a doctor's office and your boss asks you to do a new type of blood test on patients. Your boss wants to know if any of the patients have anomalous test results. However, you are not familiar with this new blood test and you do not know what normal and anomalous results are supposed to look like. All you have is a record of previous blood tests that your boss assures you are from normal patients. Suppose that these tests had the following results:

normal_results<-c(100,95,106,92,109,190,210,201,198)

Now suppose that your boss wants you to find anomalies (if any) in the following new blood test...

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Authors (2)

Alok Malik

Alok Malik is a data scientist based in India. He has previously worked on creating and deploying unsupervised learning solutions in fields such as finance, cryptocurrency trading, logistics, and natural language processing. He has a bachelor's degree in technology from the Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, where he studied electronics and communication engineering.

See other products by Alok Malik

Bradford Tuckfield

Bradford Tuckfield has designed and implemented data science solutions for firms in a variety of industries. He studied math for his bachelor's degree and economics for his Ph.D. He has written for scholarly journals and the popular press, on topics including linear algebra, psychology, and public policy.

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