Novel Approach to Evaluate Classification Algorithms and Feature Selection Filter Algorithms Using Medical Data
In today’s world, hepatitis is a widespread problem related to the medical field, which directly affects the lives of mankind. For patient survival, data mining is essential in predicting future trends using various techniques. This paper uses three feature selection filter algorithms (FSFAs): relie...
Saved in:
| Published in: | Journal of Computational and Cognitive Engineering Vol. 2; no. 1; pp. 57 - 67 |
|---|---|
| Main Authors: | , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
17.05.2022
|
| ISSN: | 2810-9570, 2810-9503 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In today’s world, hepatitis is a widespread problem related to the medical field, which directly affects the lives of mankind. For patient survival, data mining is essential in predicting future trends using various techniques. This paper uses three feature selection filter algorithms (FSFAs): relief filter, step disc filter, and Fisher filter algorithm and 15 classifiers using a free data mining Tanagra software having UCI Machine Learning Repository. This process is done on a medical dataset with 20 attributes and 155 instances. As a result, the error rate is obtained in terms of accuracy, which shows the performance of algorithms regarding patient survival. This work also shows the independent comparison of FSFAs with classification algorithms using continuous values and the FSFA without using classification algorithms. This paper shows that the obtained result of the classification algorithm gives promising results in terms of error rate and accuracy.
Received: 6 April 2022 | Revised: 12 May 2022 | Accepted: 16 May 2022
Conflicts of Interest
The authors declare that they have no conflicts of interest to this work. |
|---|---|
| ISSN: | 2810-9570 2810-9503 |
| DOI: | 10.47852/bonviewJCCE2202238 |