Clustering On Large Numeric Data Sets Using Hierarchical Approach: Birch

D. Pramodh Krishna; Dr. A. Senguttuvan; T. Swarna Latha

Clustering On Large Numeric Data Sets Using Hierarchical Approach: Birch

D. Pramodh Krishna * §

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Dr. A. Senguttuvan

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T. Swarna Latha

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§ Sree Vidyanikthan Engg. Coll., A.Rangampet, Tirupati...

Clustering On Large Numeric Data Sets Using Hierarchical Approach: Birch

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Abstract

The paper is about the clustering on large numeric data sets using hierarchical method. In this BIRCH approach is used, to reduce the amount of data, for this a hierarchical clustering method was applied to pre-process the dataset. Now a day’s web information plays a prominent role in the web technology, large amount of data is consumed to communicate, but some with intruders there is loss of data or may changes occur in the interaction, so to recognize intruders they detect to build an intrusion detection system for this a hierarchical approach is used to classify network traffic data accurately. Hierarchical clustering is performed By taking network as an example. The clustering method could produce high quality dataset with far less instances that sufficiently represent all of the instances in the original dataset.

References

8 Cites in Article

Reference Format

A Abraham,C Grosan,C Martin-Vide (2007). Evolutionary design of intrusion detection programs.
Y Bouzida,F Cuppens (2006). Neural networks vs. decision trees for intrusion detection.
S Guha,R Rastogi,K Shim (1999). ROCK: a robust clustering algorithm for categorical attributes.
S Guha,R Rastogi,K Shim (1998). Cure: An efficient clustering algorithm for large databases.
C. -W Hsu,C. -C Chang,C. -J Lin A practical guide to support vector classification.
G Karypis,Eui-Hong Han,V Kumar (1999). Chameleon: hierarchical clustering using dynamic modeling.
Kddcup (1999). Intrusion detection data set.
Latifur Khan,Mamoun Awad,Bhavani Thuraisingham (2007). A new intrusion detection system using support vector machines and hierarchical clustering.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

D. Pramodh Krishna, Dr. A. Senguttuvan, T. Swarna Latha. 2012. "Clustering On Large Numeric Data Sets Using Hierarchical Approach: Birch". Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 12 (GJCST Volume 12 Issue C12).

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GJCST Volume 12 Issue C12

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Data mining Hierarchical clustering KDD cup support vector machine

Classification

GJCST-C Classification H.3.3

Submission ReceivedDecember 13, 2011
Peer Review Double Blind
Handling Editor
Accepted January 3, 2012
Published January 15, 2012

Version of record

v1.2

Issue date

August 21, 2012

Language

English

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Article Matrices

Total Score: 148

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: D. Pramodh Krishna,Dr. A. Senguttuvan,T. Swarna Latha (PhD/Dr. count: 1)

View Count (all-time): 408

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Publish Date: 2012 01, Sun

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Total Views: 3.1K

Total Downloads: 173

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