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What is Partitional Clustering

Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems
Dissociating a data set into a set of disjoint clusters.
Published in Chapter:
Data Analytics in Industry 4.0: In the Perspective of Big Data
Mahir Oner (Istanbul Technical University, Turkey) and Sultan Ceren Oner (Istanbul Technical University, Turkey)
DOI: 10.4018/978-1-5225-2944-6.ch018
Abstract
The new form of future generation machines and automated systems could be synchronized by IoT adaptation. By this way, a very large size data can be carefully stored in data repositories and have to be analyzed for extracting knowledge. Thus, optimization techniques are becoming invaluable tools for finding patterns from parallel distributed machines. On the other hand, statistical methods and optimization models could not be utilized efficiently due to excessive dimension of data. Additionally, data analytics should be applied and results should be gathered by using practical approaches especially for security, access control and fault detection issues. In this study, optimization techniques are evaluated in the perspective of big data analytics and both mathematical and statistical methods will be extensively analyzed for different versions of problem solving and decision making in Industry 4.0 era.
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More Results
Identifying Patterns in Fresh Produce Purchases: The Application of Machine Learning Techniques
A commonly used approach to clustering that begins with a preselected number of groups or clusters. An initial allocation of objects to clusters is followed by reassignment to new groups based on a measure of proximity between each object and each group. The process continues until all objects have been assigned to their closest groups. A commonly used partitioning method is the k-means algorithm.
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Exploring the Unknown Nature of Data: Cluster Analysis and Applications
Partitional clustering directly divides data objects into some pre-specified number of clusters without the hierarchical structure.
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Full Text Chapter Download: US $37.50 Add to Cart
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