'Cluster means' diaporamas de présentation

Data Mining: Concepts and Techniques Cluster Analysis Li Xiong

Data Mining: Concepts and Techniques Cluster Analysis Li Xiong. Slide credits: Jiawei Han and Micheline Kamber Tan, Steinbach, Kumar. Chapter 7. Cluster Analysis. Overview Partitioning methods Hierarchical methods Density-based methods Other Methods Outlier analysis Summary.

2.31k views • 190 slides

Image Segmentation

Image Segmentation. Image segmentation is the operation of partitioning an image into a collection of connected sets of pixels. 1. into regions , which usually cover the image 2. into linear structures , such as - line segments - curve segments 3. into 2D shapes , such as

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Gene Regulation and Microarrays

Gene Regulation and Microarrays. Overview. A. Gene Expression and Regulation B. Measuring Gene Expression: Microarrays C. Finding Regulatory Motifs. A. Regulation of Gene Expression. Cells respond to environment. Various external messages. Heat. Responds to environmental conditions.

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For C = {a}

r 1. r 1. a. r 2. r 2. C. Gvein any function, f:X(A 1 ..A n ) ?R (any range) and any S ?R, we define contour(f,S) = f -1 (S). There is a DUALITY between functions f:X(A 1 ..A n ) ?R and derived attributes given by x.A f = f(x) or f A (x) = x.A

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COMP 578 Discovering Clusters in Databases

COMP 578 Discovering Clusters in Databases. Keith C.C. Chan Department of Computing The Hong Kong Polytechnic University. Discovering Clusters. Introduction to Clustering. Problem: Given A database of records. Each characterized by a set of attributes. To

443 views • 44 slides

For C = {a}

r 1. r 1. a. r 2. r 2. C. Gvein any function, f:X(A 1 ..A n ) ?R (any range) and any S ?R, we define contour(f,S) = f -1 (S). There is a DUALITY between functions f:X(A 1 ..A n ) ?R and derived attributes given by x.A f = f(x) or f A (x) = x.A

749 views • 41 slides

Powerpoint Templates

Autonomic Mix-Aware Provisioning on Amazon EC2 Tony Schneider, Derek Bender, Andrew Hahn Based on R. Singh et. al [1]. Powerpoint Templates. Powerpoint Templates. Introduction. Our Goals Background Implementation Results Future Work. Powerpoint Templates.

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Visualization of TV Space

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Visualization of TV Space

372 views • 37 slides

Environmental Remote Sensing GEOG 2021

Environmental Remote Sensing GEOG 2021. Lecture 5 Image classification. Purpose. categorising data data abstraction / simplification data interpretation mapping for land cover mapping

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Clustering

Clustering. What is Cluster Analysis?. Cluster: a collection of data objects Similar to one another within the same cluster Dissimilar to the objects in other clusters Cluster analysis Grouping a set of data objects into clusters

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Data Mining Comp. Sc. and Inf. Mgmt. Asian Institute of Technology

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Clustering

Clustering. Introduction K-means clustering Hierarchical clustering: COBWEB. Outline. Classification vs. Clustering. Classification: Supervised learning: Learns a method for predicting the instance class from pre-labeled (classified) instances. Clustering. Unsupervised learning:

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CSSE463: Image Recognition Day 21

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K-means

K-means. Arbitrarily choose k objects as the initial cluster centers Until no change, do (Re)assign each object to the cluster to which the object is the most similar, based on the mean value of the objects in the cluster

109 views • 5 slides