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Time Series Clustering and Classification (Chapman & Hall/CRC Computer Science & Data Analysis)
Download PDF Time Series Clustering and Classification (Chapman & Hall/CRC Computer Science & Data Analysis)
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The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website
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Product details
Series: Chapman & Hall/CRC Computer Science & Data Analysis
Hardcover: 244 pages
Publisher: Chapman and Hall/CRC; 1 edition (March 22, 2019)
Language: English
ISBN-10: 1498773214
ISBN-13: 978-1498773218
Product Dimensions:
6.1 x 9.2 inches
Shipping Weight: 1.1 pounds (View shipping rates and policies)
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Amazon Best Sellers Rank:
#1,000,603 in Books (See Top 100 in Books)
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