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Data Science Algorithms in a Week

You're reading from   Data Science Algorithms in a Week Top 7 algorithms for scientific computing, data analysis, and machine learning

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789806076
Length 214 pages
Edition 2nd Edition
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Authors (2):
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David Toth David Toth
Author Profile Icon David Toth
David Toth
David Natingga David Natingga
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David Natingga
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Table of Contents (12) Chapters Close

Preface 1. Classification Using K-Nearest Neighbors 2. Naive Bayes FREE CHAPTER 3. Decision Trees 4. Random Forests 5. Clustering into K Clusters 6. Regression 7. Time Series Analysis 8. Python Reference 9. Statistics 10. Glossary of Algorithms and Methods in Data Science
11. Other Books You May Enjoy

Swim preference – representing data using a decision tree


We may have certain preferences that determine whether or not we would swim. These can be recorded in a table, as follows:

Swimming suit

Water temperature

Swim preference

None

Cold

No

None

Warm

No

Small

Cold

No

Small

Warm

No

Good

Cold

No

Good

Warm

Yes

 

The data in this table can alternatively be presented in the following decision tree:

Figure 3.1: Decision tree for the Swim preference example

At the root node, we ask the question—do you have a swimming suit? The response to the question separates the available data into three groups, each with two rows. If the attribute is swimming suit = none, then two rows have the swim preference attribute as no. Therefore, there is no need to ask a question about the temperature of the water, as all the samples with the swimming suit = none attribute would be classified as no. This is also true for the swimming suit = small attribute. In the case of swimming suit = good, the remaining two rows can be divided into two...

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