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Hands-On Unsupervised Learning with Python

You're reading from   Hands-On Unsupervised Learning with Python Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789348279
Length 386 pages
Edition 1st Edition
Languages
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Authors (2):
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Giuseppe Bonaccorso Giuseppe Bonaccorso
Author Profile Icon Giuseppe Bonaccorso
Giuseppe Bonaccorso
Giuseppe Bonaccorso Giuseppe Bonaccorso
Author Profile Icon Giuseppe Bonaccorso
Giuseppe Bonaccorso
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Toc

Table of Contents (12) Chapters Close

Preface 1. Getting Started with Unsupervised Learning FREE CHAPTER 2. Clustering Fundamentals 3. Advanced Clustering 4. Hierarchical Clustering in Action 5. Soft Clustering and Gaussian Mixture Models 6. Anomaly Detection 7. Dimensionality Reduction and Component Analysis 8. Unsupervised Neural Network Models 9. Generative Adversarial Networks and SOMs 10. Assessments 11. Other Books You May Enjoy

Agglomerative clustering on the Water Treatment Plant dataset

Let's now consider a more detailed problem on a larger dataset (the instructions to download it are provided in the Technical requirements section at the beginning of the chapter) containing 527 samples with 38 chemical and physical variables describing the status of water treatment plants. As the same authors (Bejar, Cortes, and Poch) stated, the domain is poorly-structured and careful analysis is needed. At the same time, our goal is to find the optimal clustering with an agnostic approach; in other words, we won't consider the semantic labeling process (which needs a domain expert) but only the geometrical structure of the dataset and the relations discovered by the agglomerative algorithm.

Once downloaded, the CSV file (called water-treatment.data) can be loaded using pandas (of course, the term <DATA_PATH...

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