A Big Data Analysis Using Fuzzy Deep Convolution Network Based Model for Heart Disease Classification

Title

A Big Data Analysis Using Fuzzy Deep Convolution Network Based Model for Heart Disease Classification

Creator

Manur M.; Pani A.K.; Kumar P.

Description

Heart disease is a serious disease that causes sudden death among 80% of the people around the world. The traditional models performed predictive analytics using machine learning techniques to make a better decision. For better decision making in heart disease prediction, the big data analysis shows the great opportunities to predict the future health status from health parameters and provide best outcomes. However, the traditional decision making models had traffic data or contained noise and uncertainty was unpredictable as the data ambiguity emerged. In order to overcome such an issue, the big data is used to ensure the medical service which is mostly needed in a timely manner and for accurate diagnosis. The pre-processing of the medical data acquired from Cleveland heart disease UCI datasets has a vast number of attributes which helps to predict the heart disease. The data are contaminated with the noise and some of the data are missing, so the pre-processing using Min max Normalization is performed to remove contaminated noise acquired in the data which is taken from the UCI repository dataset. The proposed Fuzzy Deep Convolution Network (FDCN) permits the input features for fuzzification process that uses transformed features. The fuzzification process eliminates the redundant or irrelevant fuzzified features and overcomes the system complexity problems. The proposed FDCN obtains accuracy of 95.56 % and 92 % of F-score shows better results when compared with the existing KNN-DT, Naive Bayes, and Random Forest algorithms. 2021,International Journal of Intelligent Engineering and Systems. All Rights Reserved.

Source

International Journal of Intelligent Engineering and Systems, Vol-14, No. 2, pp. 147-156.

Date

2021-01-01

Publisher

Intelligent Network and Systems Society

Subject

Big data analysis; Cleveland heart disease UCI datasets; Fuzzy deep convolution network; Traffic data

Coverage

Manur M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Hyderabad, India; Pani A.K., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Hyderabad, India; Kumar P., Department of Computer Science and Technology, Motihari College of Engineering, Bihar, India

Rights

All Open Access; Bronze Open Access

Relation

ISSN: 2185310X

Format

Online

Language

English

Type

Article

Identifier

https://doi.org/10.22266/ijies2021.0430.13

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