Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology A Novel Density-Based Clustering Framework by Using Level

Intelligent Database Systems Lab

國立雲林科技大學National Yunlin University of Science and Technology

A Novel Density-Based Clustering Framework by Using Level Set Method

Presenter : Zhen-Feng Weng

Authors : Xiao-Feng Wang and De-Shuang Huang

2010/02/23

TKDE.17 (2009)

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Outline

Motivation Objective Method Experiments Conclusion Comments

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Motivation

DBSCAN is very sensitive to the selection of MinPts and Eps. The drawbacks of other approaches:

The overfitting phenomenon. The confusion between cluster boundary and noises.

Clusters

DBSCAN

Real

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Objective

It proposed a level set method for clustering. Base on the assumption that the cluster centers can be

regarded as the target objects (image segmentation).

The cluster center:To find a local maximum of density function.

The image segmentation:To find a local optimum of the intensity function.

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Concept

It applies Geometric Active Contour (GAC) model to obtain the boundaries of clusters. Elastic Evolution

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Overview

Nonparametric density estimation

Initialization of Level Set Evolution

Level Set Evolution

Level Set Density

Valley seeking

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Kernel Density Estimation & Initial Boundaries

Nonparametric density estimation:

Initialization of LSE:

Gaussian kernel

Δf(x)>0, x is inside BΔf(x)=0, x belongs BΔf(x)<0, x is outside B

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Level Set Evolution

The initial boundaries can be further divided into three types: Single-cluster, Multiple-cluster, No-cluster

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Valley Seeking

It is a graph-based theoretic clustering method. Each tree represents a cluster. According to the previous

step:

Construct the forest:

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Experiments

Comparisons with DBSCAN

DBSCANLevel Set Method

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Performance Evaluation

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Conclusions

It proposed a novel density-based clustering framework using the level set method. avoid the overfitting phenomenon. solve the confusion problem of cluster boundary

points and outliers

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Comments

Advantage A novel idea, overcome the overlap problem

Drawback Lack of demonstrations for overfitting

Application …

Documents

Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology A Novel Density-Based Clustering Framework by Using Level