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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
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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