NDLI: Hierarchical Clustering

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Hierarchical Clustering

Content Provider	Scilit
Author	Ye, Nong
Copyright Year	2013
Description	The clustering algorithms in Chapters 8 through 10 can be applied to data with one or more attribute variables. If there is only one attribute variable, we have univariate data. For univariate data, the probability distribution of data points captures not only clusters of data points but also many other characteristics concerning the distribution of data points. Many specific data patterns of univariate data can be identified through their corresponding types of probability distribution. This chapter introduces the concept and characteristics of the probability distribution and the use of the probability distribution characteristics to identify certain univariate data patterns. A list of software packages for identifying the probability distribution characteristics of univariate data is provided along with references for applications. Book Name: Data Mining
Related Links	https://content.taylorfrancis.com/books/download?dac=C2010-0-40874-6&isbn=9780429067761&doi=10.1201/b15288-11&format=pdf
Ending Page	152
Page Count	12
Starting Page	141
DOI	10.1201/b15288-11
Language	English
Publisher	Informa UK Limited
Publisher Date	2013-07-26
Access Restriction	Open
Subject Keyword	Book Name: Data Mining Artificial Intelligence Software List Packages Chapter Univariate Data Corresponding Hierarchical Attribute Variables Data Patterns
Content Type	Text
Resource Type	Chapter

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