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Clustering Techniques

Clustering Techniques

Clustering Techniques. Berlin Chen 2005. References: Introduction to Machine Learning , Chapter 7 Modern Information Retrieval , Chapters 5, 7 Foundations of Statistical Natural Language Processing , Chapter 14

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496 views • 49 slides
A New Suffix Tree Similarity Measure for Document Clustering

A New Suffix Tree Similarity Measure for Document Clustering

A New Suffix Tree Similarity Measure for Document Clustering. Hung Chim, Xiaotie Deng City University of Hong Kong WWW 2007 Session: Similarity Search. Internet Database Lab., SNU Hyewon Lim. April 11, 2008. Contents. Introduction Related Work A New Suffix Tree Similarity Measure

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534 views • 34 slides
Clustering k-mean clustering

Clustering k-mean clustering

Clustering k-mean clustering. Genome 559: Introduction to Statistical and Computational Genomics Elhanan Borenstein. A quick review. The clustering problem: partition genes into distinct sets with high homogeneity and high separation Clustering (unsupervised) vs. classification

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714 views • 31 slides
Pattern Recognition: Statistical and Neural

Pattern Recognition: Statistical and Neural

Nanjing University of Science & Technology. Pattern Recognition: Statistical and Neural. Lonnie C. Ludeman Lecture 30 Nov 11, 2005. Lecture 30 Topics. General Comments about the Clustering Problem Present my small programs that can be used for performing clustering

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291 views • 29 slides
CHAMELEON : A Hierarchical Clustering Algorithm Using Dynamic Modeling

CHAMELEON : A Hierarchical Clustering Algorithm Using Dynamic Modeling

Faculty of Electrical Engineering University of Belgrade. CHAMELEON : A Hierarchical Clustering Algorithm Using Dynamic Modeling. Student: Lazovi? Marko , 3170/11. Introduction :. Clustering in data mining is a discovery process that groups a set of data

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464 views • 26 slides
Clustering Algorithms

Clustering Algorithms

Clustering Algorithms. Mu-Yu Lu. What is Clustering?. Clustering can be considered the most important unsupervised learning problem; so, as every other problem of this kind, it deals with finding a structure in a collection of unlabeled data.

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390 views • 23 slides

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