'Cluster quality' presentation slideshows

Data Mining (and machine learning)

Data Mining (and machine learning). DM Lecture 5: Clustering. Today. (unsupervised) Clustering What and why A good first step towards understanding your data Discover patterns and structure in data Which then guides further data mining Helps to spot problems and outliers

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431 views • 42 slides

K-means clustering

CZ5225: Modeling and Simulation in Biology Lecture 4: Clustering Analysis for Microarray Data II Prof. Chen Yu Zong Tel: 6874-6877 Email: yzchen@cz3.nus.edu.sg http://xin.cz3.nus.edu.sg Room 07-24, level 7, SOC1, NUS. K-means clustering. This method differs from the hierarchical clustering

469 views • 42 slides

Pseudo-supervised Clustering for Text Documents

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Clustering

Clustering. Patrice Koehl Department of Biological Sciences National University of Singapore. http://www.cs.ucdavis.edu/~koehl/Teaching/BL5229 dbskoehl@nus.edu.sg. Clustering is a hard problem. Many possibilities; What is best clustering ?. Clustering is a hard problem. 2 clusters: easy.

246 views • 24 slides

Clustering

Clustering. Patrice Koehl Department of Biological Sciences National University of Singapore. http://www.cs.ucdavis.edu/~koehl/Teaching/BL5229 dbskoehl@nus.edu.sg. Clustering is a hard problem. Many possibilities; What is best clustering ?. Clustering is a hard problem. 2 clusters: easy.

244 views • 24 slides

CLEVER: CL ust E ring using representati VE s and R andomized hill climbing

290 views • 13 slides