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## You're reading fromPython Machine Learning (Wiley)

Product type Book
Published in Apr 2019
Publisher Wiley
ISBN-13 9781119545637
Pages 320 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Wei-Meng Lee

1. Cover
2. Introduction
3. CHAPTER 1: Introduction to Machine Learning 4. CHAPTER 2: Extending Python Using NumPy 5. CHAPTER 3: Manipulating Tabular Data Using Pandas 6. CHAPTER 4: Data Visualization Using matplotlib 7. CHAPTER 5: Getting Started with Scikit‐learn for Machine Learning 8. CHAPTER 6: Supervised Learning—Linear Regression 9. CHAPTER 7: Supervised Learning—Classification Using Logistic Regression 10. CHAPTER 8: Supervised Learning—Classification Using Support Vector Machines 11. CHAPTER 9: Supervised Learning—Classification Using K‐Nearest Neighbors (KNN) 12. CHAPTER 10: Unsupervised Learning—Clustering Using K‐Means 13. CHAPTER 11: Using Azure Machine Learning Studio 14. CHAPTER 12: Deploying Machine Learning Models 15. Index

# What Is Unsupervised Learning?

So far, all of the machine learning algorithms that you have seen are supervised learning. That is, the datasets have all been labeled, classified, or categorized. Datasets that have been labeled are known as labeled data, while datasets that have not been labeled are known as unlabeled data. Figure 10.1 shows an example of labeled data.

Based on the size of the house and the year in which it was built, you have the price at which the house was sold. The selling price of the house is the label, and your machine learning model can be trained to give the estimated worth of the house based on its size and the year in which it was built.

Unlabeled data, on the other hand, is data without label(s). For example, Figure 10.2 shows a dataset containing a group of people's waist circumference and corresponding leg length. Given this set of data, you can try to cluster them into groups based on the waist circumference and leg length...

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