Tuesday, February 9, 2016

Data Mining - Clustering



Applications of Cluster Analysis

Clustering analysis is  used in applications such as market research, pattern recognition, data analysis, and image processing.

Clustering can also help marketers discover distinct groups (Segmentation)  based on the purchasing patterns in their customer base.

In the field of biology, it can be used to derive plant and animal taxonomies, categorize genes with similar functionalities and gain insight into structures inherent to populations.

Clustering also helps in identification of areas of similar land use in an earth observation database. It also helps in the identification of groups of houses in a city according to house type, value, and geographic location.

Clustering also helps in classifying documents on the web for information discovery.

Clustering is also used in outlier detection applications such as detection of credit card fraud.

As a data mining function, cluster analysis serves as a tool to gain insight into the distribution of data to observe characteristics of each cluster.

Mod-03 Lec-25 Basics of Clustering, Similarity/Dissimilarity Measures, Clustering Criteria.



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