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| fixed length control field |
01191nam a22001457a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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210806b ||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--AUTHOR |
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| Author |
AKPU, CHUKWUMA HILARY |
| 245 ## - TITLE STATEMENT |
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| Title |
A PREDICTIVE MODEL FOR THE DIAGNOSIS OF HEART DISEASE WITH THE USE OF MACHINE LEARNING TECHNIQUES |
| 250 ## - SUPERVISOR |
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| Supervisor |
DR. F. A. KASALI |
| 260 ## - IMPRINT |
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| Place of publication |
Ibafo |
| Department (College) |
COMPUTER SCIENCE AND MATHEMATICS |
| Date of publication |
2020 |
| 300 ## - COLLATION |
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| Pagination |
ix; 50 |
| Other physical details |
dia, tables |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Heart diseases have the highest death toll since 2000. Heart disease on its own is basically a deficiency in the heart of living things and there are multiple kinds of heart diseases such as arrhythmia, atherosclerosis, congenital heart defects, coronary artery disease among many others. This study aims to use machine learning techniques ranging from feature selection, principal component analysis, cross-validation and several machine learning algorithms.<br/> Historical data on the distribution of heart disease among patients have been gathered and I acquired this data to be used in this research study. The predictive model for diagnosing heart diseases was developed using several machine learning algorithms. <br/> |
| 650 ## - TRACINGS |
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| Main Subject |
Computer Science |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Item type |
Students Thesis |
