Classification Model for the Heart Disease Diagnosis

Atul Kumar Pandey; Prabhat Pandey; K.L. Jaiswal

Classification Model for the Heart Disease Diagnosis

Atul Kumar Pandey * §

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Prabhat Pandey

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K.L. Jaiswal

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§ APS University, Rewa(M.P.)-India

Classification Model for the Heart Disease Diagnosis

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Abstract

Medical science industry has huge amount of data, but unfortunately most of this data is not mined to find out hidden information in data. Advanced data mining techniques can be used to discover hidden pattern in data. Models developed from these techniques will be useful for medical practitioners to take effective decision. In this research work, we have analyzed the performance of the classification rule algorithms namely PART based on K-Means Clustering algorithms. The k-means is the simplest, most commonly and good behavior clustering algorithm used in many applications. Firstly the preprocessed heart disease dataset is grouped using the K-means algorithm with the K =2 values on classes to cluster evaluation testing mode. After that data mining classification rule algorithms namely Projective Adaptive Resonance Theory are analyzed on clustered relevant dataset. In our studies 10-fold cross validation method was used to measure the unbiased estimate of the prediction model. Accuracy of K-Means Clustering, PART and PART based on K-Means Clustering are 81.08%, 79.05% and 84.12% respectively.

References

13 Cites in Article

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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

Atul Kumar Pandey, Prabhat Pandey, K.L. Jaiswal. 2014. "Classification Model for the Heart Disease Diagnosis". Global Journal of Medical Research - F: Diseases GJMR-F Volume 14 (GJMR Volume 14 Issue F1).

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GJMR Volume 14 Issue F1

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Journal Specifications

Crossref Journal DOI 10.17406/gjmr

Print ISSN 0975-5888

e-ISSN 2249-4618

Keywords

and part classification rules data mining techniques heart disease K-Means Clustering

Classification

GJMR-F Classification NLMC Code: WG 200

WG 205

Submission ReceivedDecember 10, 2013
Peer Review Double Blind
Handling Editor
Accepted January 4, 2014
Published January 15, 2014

Version of record

v1.2

Issue date

April 29, 2014

Language

English

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Article Matrices

Total Score: 143

Country: India

Subject: Global Journal of Medical Research

Authors: Atul Kumar Pandey, Prabhat Pandey, K.L. Jaiswal (PhD/Dr. count: 0)

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Publish Date: 2014 01, Wed

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Total Views: 2K

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