'Random data random points' diaporamas de présentation

DATA MINING LECTURE 8

DATA MINING LECTURE 8. The EM Algorithm Clustering Validation Sequence segmentation. CLUSTERING. Inter-cluster distances are maximized. Intra-cluster distances are minimized. What is a Clustering ?.

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DATA MINING LECTURE 8

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Critical Issues with Respect to Clustering

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Cluster Analysis

Cluster Analysis. Midterm: Monday Oct 29, 4PM. Lecture Notes from Sept 5, 2007 until Oct 15, 2007. Chapters from Textbook and papers discussed in class (see below detailed list) Specific Readings Textbook: Chapter 1 Chapter 2: 2.1- 2.4 Chapter 3: 3.1-3.4

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Clustering V

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Cluster Validation

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Cluster Analysis

Cluster Analysis. Cluster Analysis. What is Cluster Analysis? Types of Data in Cluster Analysis A Categorization of Major Clustering Methods Partitioning Methods Hierarchical Methods Density-Based Methods Grid-Based Methods Model-Based Clustering Methods. Model based clustering.

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Cluster Validation

Cluster Validation. Cluster validation Assess the quality and reliability of clustering results. Why validation? To avoid finding clusters formed by chance To compare clustering algorithms To choose clustering parameters e.g., the number of clusters in the K-means algorithm. DBSCAN.

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