dm5part3 - University of Florida CISE department Gator...

Info iconThis preview shows pages 1–6. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: University of Florida CISE department Gator Engineering Clustering Part 3 Dr. Sanjay Ranka Professor Computer and Information Science and Engineering University of Florida, Gainesville University of Florida CISE department Gator Engineering Data Mining Sanjay Ranka Spring 2011 Hierarchical Clustering Two main types: Agglomerative Start with the points as individual clusters Merge clusters until only one is left Divisive Start with all the points as one cluster Split clusters until only singleton clusters remain Agglomerative is more popular Traditional hierarchical algorithms use a similarity or distance matrix. Merge or split one cluster at a time University of Florida CISE department Gator Engineering Data Mining Sanjay Ranka Spring 2011 Hierarchical Clustering Produces a set of nested clusters organized as a hierarchical tree. Can be visualized as a dendrogram Tree like diagram Records the sequences of merges or splits Can cut the dendrogram to get a partitional clustering University of Florida CISE department Gator Engineering Data Mining Sanjay Ranka Spring 2011 Basic Agglomerative Clustering Algorithm Algorithm is straightforward Compute the proximity matrix, if necessary Let each data point be a cluster Repeat Merge the two closest clusters Update the proximity matrix Until only a single cluster remains Key operation is the computation of the proximity of two clusters. Different approaches to defining the distance between clusters distinguishes the different algorithms. University of Florida CISE department Gator Engineering Data Mining Sanjay Ranka Spring 2011 Agglomerative Hierarchical Clustering: Starting Situation For agglomerative hierarchical clustering we start with clusters of individual points and a proximity matrix. p1 p3 p5 p4 p2 p1 p2 p3 p4 p5 . . ....
View Full Document

This note was uploaded on 11/13/2011 for the course CIS 4930 taught by Professor Staff during the Spring '08 term at University of Florida.

Page1 / 27

dm5part3 - University of Florida CISE department Gator...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online