Reference Hub

This research has been cited in:

Article
Smart-Hydroponic-Based Framework for Saffron Cultivation: A Precision Smart Agriculture PerspectiveSustainability10.3390/su14031120
Chapter
Efficient‐driven Approaches Related to Meta‐Heuristic Algorithms using Machine Learning TechniquesMeta Heuristic Algorithms for Advanced Distributed Systems10.1002/9781394188093.ch6
Conference
Brain Tumor Detection Using Fish Schooling Genetic Algorithm2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO51393.2021.9596094
Article
A Deep Analysis of Brain Tumor Detection from MR Images Using Deep Learning NetworksAlgorithms10.3390/a16040176
Article
CNN Based Multiclass Brain Tumor Detection Using Medical ImagingComputational Intelligence and Neuroscience10.1155/2022/1830010
Article
Transfer learning-based modified inception model for the diagnosis of Alzheimer's diseaseFrontiers in Computational Neuroscience10.3389/fncom.2022.1000435
Article
Optimized CNN-Based Recognition of District Names of Punjab State in Gurmukhi ScriptJournal of Mathematics10.1155/2022/6580839
Conference
A Robust Watermarking Algorithm for Exchange Ciphers Using Homomorphic Encryption2022 2nd International Conference on Networking, Communications and Information Technology (NetCIT)10.1109/NetCIT57419.2022.00135
Article
A Fog-Cluster Based Load-Balancing TechniqueSustainability10.3390/su14137961
Conference
The Use of Encryption to Preserve the Privacy and Security of Electronic Health Records2023 International Conference on Business Analytics for Technology and Security (ICBATS)10.1109/ICBATS57792.2023.10111147
Article
Performance Evaluation of the Deep Learning Based Convolutional Neural Network Approach for the Recognition of Chest X-Ray ImagesFrontiers in Oncology10.3389/fonc.2022.932496
Conference
IoT enabled obstruction evasion Robots for enhancing the security of the Systems2023 International Conference on Artificial Intelligence and Smart Communication (AISC)10.1109/AISC56616.2023.10085000
Article
Controlling Agronomic Variables of Saffron Crop Using IoT for Sustainable AgricultureSustainability10.3390/su14095607
Conference
Identification of Heart Diseases using Novel Machine Learning Method2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)10.1109/ACCAI58221.2023.10200215
Article
Segmentation and Classification of Encephalon Tumor by Applying Improved Fast and Robust FCM Algorithm with PSO-Based ELM TechniqueComputational Intelligence and Neuroscience10.1155/2022/2664901
Conference
Heart Disease Predictive Analysis Using Machine Learning Approaches2023 6th International Conference on Contemporary Computing and Informatics (IC3I)10.1109/IC3I59117.2023.10397609
Chapter
Implementation and Analysis of the Proposed Model in a Distributede‐Healthcare SystemMeta Heuristic Algorithms for Advanced Distributed Systems10.1002/9781394188093.ch8
Article
An Approach for Thoracic Syndrome Classification with Convolutional Neural NetworksComputational and Mathematical Methods in Medicine10.1155/2021/3900254
Article
Image Retrieval Using Different Distance Methods and Color Difference Histogram Descriptor for Human HealthcareJournal of Healthcare Engineering10.1155/2022/9523009
Article
IoT-Based Technological Framework for Inhibiting the Spread of COVID-19: A Pandemic Using Machine Learning and Fuzzy-Based ProcessesSecurity and Communication Networks10.1155/2022/6272480
Article
Using Identity-Based Cryptography as a Foundation for an Effective and Secure Cloud Model for E-HealthComputational Intelligence and Neuroscience10.1155/2022/7016554
Article
An Artificial Intelligence-Based Stacked Ensemble Approach for Prediction of Protein Subcellular Localization in Confocal Microscopy ImagesSustainability10.3390/su15021695

Kernel Parameter Tuning to Tweak the Performance of Classifiers for Identification of Heart Diseases

Annu Dhankhar, Sapna Juneja, Abhinav Juneja, Vikram Bali

Source Title: International Journal of E-Health and Medical Communications (IJEHMC)12(4)

ISSN: 1947-315X|EISSN: 1947-3168|EISBN13: 9781799861577|DOI: 10.4018/IJEHMC.20210701.oa1

Cite Article Cite Article

MLA

Dhankhar, Annu, et al. "Kernel Parameter Tuning to Tweak the Performance of Classifiers for Identification of Heart Diseases." IJEHMC vol.12, no.4 2021: pp.1-16. http://doi.org/10.4018/IJEHMC.20210701.oa1

APA

Dhankhar, A., Juneja, S., Juneja, A., & Bali, V. (2021). Kernel Parameter Tuning to Tweak the Performance of Classifiers for Identification of Heart Diseases. International Journal of E-Health and Medical Communications (IJEHMC), 12(4), 1-16. http://doi.org/10.4018/IJEHMC.20210701.oa1

Chicago

Dhankhar, Annu, et al. "Kernel Parameter Tuning to Tweak the Performance of Classifiers for Identification of Heart Diseases," International Journal of E-Health and Medical Communications (IJEHMC) 12, no.4: 1-16. http://doi.org/10.4018/IJEHMC.20210701.oa1

Export Reference

Favorite Full-Issue Download

View Full Text HTML

View Full Text PDF

Abstract

Medical data analysis is being recognized as a field of enormous research possibilities due to the fact there is a huge amount of data available and prediction in initial stage may save patient lives with timely intervention. With machine learning, a particular algorithm may be created through which any disease may be predicted well in advance on the basis of its feature sets or its symptoms can be detected. With respect to this research work, heart disease will be predicted with support vector machine that falls under the category of supervised machine learning algorithm. The main idea of this study is to focus on the significance of parameter tuning to elevate the performance of classifier. The results achieved were then compared with normal classifier SVM before tuning the parameters. Results depict that the hyperparameters tuning enhances the performance of the model. Finally, results were calculated by using various validation metrics.