Cluster Analysis in Data Mining

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5

(8)

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Course Features

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Duration

17 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

17 hours

Course Description

Learn the basics of cluster analysis and then examine a variety of common clustering algorithms and methods. These include hierarchical methods like BIRCH and partitioning methods like k-means. Learn how to validate clustering and evaluate clustering quality. Finally, you can see examples of cluster analysis within applications.

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Applications of Cluster Analysis

K-Means Clustering MethodHierarchical Clustering Methods

Course Instructors

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Jiawei Han

Abel Bliss Professor

Jiawei Han is Abel Bliss Professor in the Department of Computer Science at the University of Illinois. He received his Ph.D. in Computer Sciences at University of Wisconsin in 1985. He worked as ass...

Course Reviews

Average Rating Based on 8 reviews

4.9

88%

13%

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