'Cluster centroids' presentation slideshows

Chapter 6: Segmentation

Chapter 6: Segmentation. Chapter 6: Segmentation. Objectives. Define pattern discovery. Name some of the statistical and analytical techniques that are useful for pattern discovery. Pattern Discovery. The Essence of Data Mining?

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Clustering

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Expert Object Recognition in Video

Expert Object Recognition in Video. Matt McEuen. Ventral Visual Pathway. EOR Pathway. From Draper, Baek, Boody - 2002. The EOR Pathway. Early vision (feature extraction) Categorization Exemplar matching. Feature Extraction. Clustering. Exemplar Matching. Expert Object Recognition.

635 views • 47 slides

Cluster Analysis & Hybrid Models Business Application & Conceptual Issues March 3, 2005

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Cluster Analysis & Hybrid Models Business Application & Conceptual Issues Oct 4, 2005

576 views • 45 slides

Machine Learning

454 views • 39 slides

Clustering

Machine Learning. Clustering. Unsupervised Learning K-means Optimization objective Random initialization Determining Number of Clusters Hierarchical Clustering Soft Clustering (Fuzzy C-Means). References.

364 views • 36 slides

Large-scale Single-pass k-Means Clustering at Scale

Large-scale Single-pass k-Means Clustering at Scale. Large-scale Single-pass k-Means Clustering. Large-scale k -Means Clustering. Goals. Cluster very large data sets Facilitate large nearest neighbor search Allow very large number of clusters Achieve good quality

523 views • 30 slides

HJ -Hadoop An Optimized MapReduce Runtime for Multi-core Systems

HJ -Hadoop An Optimized MapReduce Runtime for Multi-core Systems. Yunming Zhang Advised by: Prof. Alan Cox and Vivek Sarkar Rice University. Social Informatics. Big Data Era. 2008. 20 PB/day. 100 PB media. 2012. 120 PB cluster. 2011. Bing ~ 300 PB. 2012. MapReduce Runtime. Map.

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A modified version of the K-means algorithm with a distance based on cluster symmetry

A modified version of the K-means algorithm with a distance based on cluster symmetry. Advisor ? Dr. Hsu Reporter ? Chun Kai Chen Author ? Mu-Chun Su and Chien-Hsing Chou. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2001. Outline. Motivation Objective Introduction

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The 5th annual UK Workshop on Computational Intelligence London, 5-7 September 2005

The 5th annual UK Workshop on Computational Intelligence London, 5-7 September 2005. Learning Topic Hierarchies from Text Documents using a Scalable Hierarchical Fuzzy Clustering Method. E. Mendes Rodrigues and L. Sacks {mmendes, lsacks}@ee.ucl.ac.uk http://www.ee.ucl.ac.uk/~mmendes/.

295 views • 15 slides

K-means algorithm

Speech and Image Processing Unit School of Computing University of Eastern Finland. K-means algorithm. Clustering Methods: Part 2a. Pasi Fränti. K- m eans overview. Well-known clustering algorithm Number of clusters must be chosen in advance Strengths:

307 views • 10 slides