Automatically assigned DDC number: 006312

Manually assigned DDC number: 006312

Number of references: 16

Title: FindOut: Finding Outliers in Very Large Datasets

Author:

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Subject: Dantong Yu,Gholam Sheikholeslami,Aidong Zhang FindOut: Finding Outliers in Very Large Datasets

Description: Signal processing techniques have been introduced to transform images for image enhancement, filtering and restoration, analysis, and reconstruction. In this paper, we apply signal processing techniques to solve important KDD problems. In particular, we introduce a novel deviation (or outlier) detection approach, termed FindOut, based on wavelet transform. The main idea in FindOut is to remove the clusters from the original data and then identify the outliers. Although previous research showed that such techniques may not be effective because of the nature of the clustering, FindOut can successfully identify various percentages of outliers from large datasets. Thus, we can combine both clustering and outliers detection in a unified approach. Experimental results on very large datasets are presented which show the efficiency and effectiveness of the proposed approach. 1 Introduction Data mining is a process of extracting valid, previously unknown, and ultimately comprehensible informat...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1999-07-01

Pubyear: 1999

Format: ps

Identifier: http://citeseer.ist.psu.edu/230290.html

Source: ftp://ftp.cs.buffalo.edu/pub/tech-reports/99-03.ps.Z

Language: en

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