Performance Analysis of PCA, Sparse PCA, Kernel PCA and Incremental PCA Algorithms for Heart Failure Prediction

Atiqur Rehman, Aurangzeb Khan, Akhtar Ali, Muhammad Umair Khan, Shafqat Ullah Khan, Liaqat Ali

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Heart failure (HF) prediction is a challenging issue in medical informatics and is considered a deadliest disease worldwide. Recent research has been concentrated on features transformation and selection for improved HF prediction. In this study, we search optimal feature extraction algorithm by evaluating the performance of different feature extraction algorithms namely Principle Component Analysis (PCA), Sparse PCA, Kernel PCA and Incremental PCA. These algorithms are integrated with machine learning models to improve HF prediction. The performance of all these integrated models are evaluated by analyzing Cleveland heart failure database. Experimental results pointed out that Kernel PCA algorithm integrated with linear discriminant analysis model and Sparse PCA integrated with Gaussian Naive Bayes (GNB) model offers 91.11% of HF classification accuracy. Hence, based on the experimental results it is shown that Kernel PCA and Sparse PCA are suitable feature extraction methods for HF data.
Original languageEnglish
Title of host publication2nd International Conference on Electrical, Communication and Computer Engineering
Subtitle of host publicationICECCE 2020)
Place of PublicationPiscataway
PublisherIEEE
Number of pages5
ISBN (Electronic)9781728171173
ISBN (Print)9781728171166, 9781728171159
DOIs
Publication statusPublished - Jun 2020
Event2nd International Conference on Electrical, Communication and Computer Engineering - Istanbul, Turkey
Duration: 12 Jun 202013 Jun 2020
http://icecce.com/

Conference

Conference2nd International Conference on Electrical, Communication and Computer Engineering
Abbreviated titleICECCE 2020
CountryTurkey
CityIstanbul
Period12/06/2013/06/20
Internet address

Fingerprint

Dive into the research topics of 'Performance Analysis of PCA, Sparse PCA, Kernel PCA and Incremental PCA Algorithms for Heart Failure Prediction'. Together they form a unique fingerprint.

Cite this