A Comparative Study of Building Disease Classification Model through Supervised Machine Learning Algorithms for HealthCare Data
| Author(s) | : | Anjali Choudhary, Shrwan Ram |
| Institution | : | Computer Science Department, M.B.M. Engineering College Jodhpur |
| Published In | : | Vol. 7, Issue 10 — October 2020 |
| Page No. | : | 42-48 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
With the emerging new disease patterns, new technologies like machine learning and data analytics areproving to provide promising solutions in early detection of symptoms, decoding various patterns, predicting variousresponses to drugs, etc. These are proving to be very helpful to biomedical professionals, the healthcare industry, andpatients. Machine learning can be used to develop models for the prediction of chronic diseases.In this paper, machine learning techniques will be compared using the benchmark datasets. The different types of dataclassification methods and techniques are available such as Decision Tree, k-Nearest Neighbor, Support VectorMachine, Naive Bayes, Logistic Regression, and Linear Discriminant algorithms. The objective of the thesis work is todo the comparative study and evaluation of supervised machine learning methods with the help of reduced healthcaredatasets collected. It is shown that the accuracy of the SVM classifier is better than the others.
Anjali Choudhary, Shrwan Ram, “A Comparative Study of Building Disease Classification Model through Supervised Machine Learning Algorithms for HealthCare Data”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 10, pp. 42-48, October 2020.
