Chronic kidney disease detection using ensemble classi ers and feature set reduction
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.
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| Idioma: | English |
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BRAC University
2019
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| Acesso em linha: | http://hdl.handle.net/10361/12255 |
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10361-122552022-01-26T10:20:04Z Chronic kidney disease detection using ensemble classi ers and feature set reduction Shawan, Naveed Rahman Mehrab, Syed Samiul Alam Ahmed, Fardeen Hasmi, Mohammad Sharatul Arif, Hossain Mobin, Md. Iftekharul Department of Computer Science and Engineering, Brac University Ensemble learning Imbalanced dataset Chronic kidney disease Machine learning Machine learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (page 40). Chronic kidney disease (CKD) is the gradual loss of kidney function over a duration of months or years. One in ten people are affected by it at some stage. Some ethnicities such as African Americans and South Asians are predisposed to having the disease. Globally the number of people affected has been growing through the years, with 752.7 million having the disease in 2016 The disease has no cure, so early detection is key to better manage the disease and control other risk factors such as diabetes and blood pressure. Although CKD has no early symptoms and requires medical tests on blood and/or urine samples, medical tests conducted for other diseases hold clues to whether someone has CKD . The datasets that are available have a multitude of features and are also incomplete and imbalanced. We want to overcome this problems through feature engineering to reduce the number of features. A comparative study of various classifiers needs to be done to find those that hold promise and are robust enough to handle currently available datasets, which are both incomplete and unbalanced. Our study is to bring down the number of attributes/features using recursive feature elimination method and use Ensemble classifier to predict the existence of CKD from the reduced features. Naveed Rahman Shawan Syed Samiul Alam Mehrab Fardeen Ahmed Mohammad Sharatul Hasmi B. Computer Science and Engineering 2019-06-25T10:00:08Z 2019-06-25T10:00:08Z 2019 2019 Thesis ID 13201027 ID 16101175 ID 15101073 ID 15101133 http://hdl.handle.net/10361/12255 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 41 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Ensemble learning Imbalanced dataset Chronic kidney disease Machine learning Machine learning |
| spellingShingle |
Ensemble learning Imbalanced dataset Chronic kidney disease Machine learning Machine learning Shawan, Naveed Rahman Mehrab, Syed Samiul Alam Ahmed, Fardeen Hasmi, Mohammad Sharatul Chronic kidney disease detection using ensemble classi ers and feature set reduction |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019. |
| author2 |
Arif, Hossain |
| author_facet |
Arif, Hossain Shawan, Naveed Rahman Mehrab, Syed Samiul Alam Ahmed, Fardeen Hasmi, Mohammad Sharatul |
| format |
Thesis |
| author |
Shawan, Naveed Rahman Mehrab, Syed Samiul Alam Ahmed, Fardeen Hasmi, Mohammad Sharatul |
| author_sort |
Shawan, Naveed Rahman |
| title |
Chronic kidney disease detection using ensemble classi ers and feature set reduction |
| title_short |
Chronic kidney disease detection using ensemble classi ers and feature set reduction |
| title_full |
Chronic kidney disease detection using ensemble classi ers and feature set reduction |
| title_fullStr |
Chronic kidney disease detection using ensemble classi ers and feature set reduction |
| title_full_unstemmed |
Chronic kidney disease detection using ensemble classi ers and feature set reduction |
| title_sort |
chronic kidney disease detection using ensemble classi ers and feature set reduction |
| publisher |
BRAC University |
| publishDate |
2019 |
| url |
http://hdl.handle.net/10361/12255 |
| work_keys_str_mv |
AT shawannaveedrahman chronickidneydiseasedetectionusingensembleclassiersandfeaturesetreduction AT mehrabsyedsamiulalam chronickidneydiseasedetectionusingensembleclassiersandfeaturesetreduction AT ahmedfardeen chronickidneydiseasedetectionusingensembleclassiersandfeaturesetreduction AT hasmimohammadsharatul chronickidneydiseasedetectionusingensembleclassiersandfeaturesetreduction |
| _version_ |
1814309192429731840 |