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Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining

Finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups. Understanding Group related documents for browsing, group genes and proteins that have similar functionality, or group stocks with similar price fluctuations Summarization Reduce the size of large data sets | Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining by Tan, Steinbach, Kumar © Tan,Steinbach, Kumar Introduction to Data Mining What is Cluster Analysis? Finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups Inter-cluster distances are maximized Intra-cluster distances are minimized Applications of Cluster Analysis Understanding Group related documents for browsing, group genes and proteins that have similar functionality, or group stocks with similar price fluctuations Summarization Reduce the size of large data sets Clustering precipitation in Australia What is not Cluster Analysis? Supervised classification Have class label information Simple segmentation Dividing students into different registration groups alphabetically, by last name Results of a query Groupings are a result of an external . | Data Mining Cluster Analysis: Basic Concepts and Algorithms Lecture Notes for Chapter 8 Introduction to Data Mining by Tan, Steinbach, Kumar © Tan,Steinbach, Kumar Introduction to Data Mining What is Cluster Analysis? Finding groups of objects such that the objects in a group will be similar (or related) to one another and different from (or unrelated to) the objects in other groups Inter-cluster distances are maximized Intra-cluster distances are minimized Applications of Cluster Analysis Understanding Group related documents for browsing, group genes and proteins that have similar functionality, or group stocks with similar price fluctuations Summarization Reduce the size of large data sets Clustering precipitation in Australia What is not Cluster Analysis? Supervised classification Have class label information Simple segmentation Dividing students into different registration groups alphabetically, by last name Results of a query Groupings are a result of an external specification Graph partitioning Some mutual relevance and synergy, but areas are not identical Notion of a Cluster can be Ambiguous How many clusters? Four Clusters Two Clusters Six Clusters Types of Clusterings A clustering is a set of clusters Important distinction between hierarchical and partitional sets of clusters Partitional Clustering A division data objects into non-overlapping subsets (clusters) such that each data object is in exactly one subset Hierarchical clustering A set of nested clusters organized as a hierarchical tree Partitional Clustering Original Points A Partitional Clustering Hierarchical Clustering Traditional Hierarchical Clustering Non-traditional Hierarchical Clustering Non-traditional Dendrogram Traditional Dendrogram Other Distinctions Between Sets of Clusters Exclusive versus non-exclusive In non-exclusive clusterings, points may belong to multiple clusters. Can represent multiple classes or ‘border’ points Fuzzy versus non-fuzzy In fuzzy clustering, a point .