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What is Classifi cation

Handbook of Research on Developments in E-Health and Telemedicine: Technological and Social Perspectives
Automated classification tools such as decision trees have been shown to be very effective for distinguishing and characterizing very large volumes of data. They assign items to one of a set of predefined classes of objects based on a set of observed features. Classifiers can be learned automatically from a set of examples through supervised learning. Classification rules are rules that discriminate between different partitions of a database based on various attributes within the database. The partitions of the database are based on an attribute called the classification label.
Published in Chapter:
Electrocardiographic Signal Processing Applications in Telemedicine
Adrian Brezulianu (“Gheorghe Asachi” Technical University, Romania), Iulian Ciocoiu (“Gheorghe Asachi” Technical University, Romania), and Monica Fira (Institute for Theoretical Computer Science, Romania)
DOI: 10.4018/978-1-61520-670-4.ch010
Abstract
The chapter focuses on telecardiology, as a significant example of telemedicine applications. Essential elements regarding the benefits and importance of telemedicine are presented first, followed by the introduction of specific telecardiology terminology, theoretical grounds, and existing practical applications. In the final part of the chapter new practical approaches are outlined, mainly related to modern signal processing tools such as wavelet analysis and neural networks.
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Association Rule Mining
Data mining technique that constructs a model (classifier) from historical data (training data) and uses it to predict the category of unseen tuples.
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